1992-08-01
Rychlik J.: Simulation of distributed control systems. Research report of Institute of Technology in 22 Pilsen no. 209-07-85, Jun. 1985 Kocur P... Kocur P.: Sensitivity analysis of reliability parameters. Proceedings of conf. FTSD, Brno, Jun. 1986, pp. 97-101 Smrha P., Kocur P., Racek S.: A
Secure and Efficient Network Fault Localization
2012-02-27
ORGANIZATION NAME(S) AND ADDRESS (ES) Carnegie Mellon University,School of Computer Science,Computer Science Department,Pittsburgh,PA,15213 8. PERFORMING...ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS (ES) 10. SPONSOR/MONITOR’S ACRONYM(S) 11. SPONSOR/MONITOR’S REPORT...efficiency than previously known protocols for fault localization. Our proposed fault localization protocols also address the security threats that
Computers in Academic Architecture Libraries.
ERIC Educational Resources Information Center
Willis, Alfred; And Others
1992-01-01
Computers are widely used in architectural research and teaching in U.S. schools of architecture. A survey of libraries serving these schools sought information on the emphasis placed on computers by the architectural curriculum, accessibility of computers to library staff, and accessibility of computers to library patrons. Survey results and…
2010-06-01
DATES COVEREDAPR 2009 – JAN 2010 (From - To) APR 2009 – JAN 2010 4. TITLE AND SUBTITLE EMERGING NEUROMORPHIC COMPUTING ARCHITECTURES AND ENABLING...14. ABSTRACT The highly cross-disciplinary emerging field of neuromorphic computing architectures for cognitive information processing applications...belief systems, software, computer engineering, etc. In our effort to develop cognitive systems atop a neuromorphic computing architecture, we explored
Memristor-Based Synapse Design and Training Scheme for Neuromorphic Computing Architecture
2012-06-01
system level built upon the conventional Von Neumann computer architecture [2][3]. Developing the neuromorphic architecture at chip level by...SCHEME FOR NEUROMORPHIC COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-11-2-0046 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...creation of memristor-based neuromorphic computing architecture. Rather than the existing crossbar-based neuron network designs, we focus on memristor
Developing a Distributed Computing Architecture at Arizona State University.
ERIC Educational Resources Information Center
Armann, Neil; And Others
1994-01-01
Development of Arizona State University's computing architecture, designed to ensure that all new distributed computing pieces will work together, is described. Aspects discussed include the business rationale, the general architectural approach, characteristics and objectives of the architecture, specific services, and impact on the university…
Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures
2017-10-04
Report: Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures The views, opinions and/or findings contained in this...Chapel Hill Title: Efficient Numeric and Geometric Computations using Heterogeneous Shared Memory Architectures Report Term: 0-Other Email: dm...algorithms for scientific and geometric computing by exploiting the power and performance efficiency of heterogeneous shared memory architectures . These
Frances: A Tool for Understanding Computer Architecture and Assembly Language
ERIC Educational Resources Information Center
Sondag, Tyler; Pokorny, Kian L.; Rajan, Hridesh
2012-01-01
Students in all areas of computing require knowledge of the computing device including software implementation at the machine level. Several courses in computer science curricula address these low-level details such as computer architecture and assembly languages. For such courses, there are advantages to studying real architectures instead of…
Tutorial: Computer architecture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gajski, D.D.; Milutinovic, V.M.; Siegel, H.J.
1986-01-01
This book presents the state-of-the-art in advanced computer architecture. It deals with the concepts underlying current architectures and covers approaches and techniques being used in the design of advanced computer systems.
Outline of a novel architecture for cortical computation.
Majumdar, Kaushik
2008-03-01
In this paper a novel architecture for cortical computation has been proposed. This architecture is composed of computing paths consisting of neurons and synapses. These paths have been decomposed into lateral, longitudinal and vertical components. Cortical computation has then been decomposed into lateral computation (LaC), longitudinal computation (LoC) and vertical computation (VeC). It has been shown that various loop structures in the cortical circuit play important roles in cortical computation as well as in memory storage and retrieval, keeping in conformity with the molecular basis of short and long term memory. A new learning scheme for the brain has also been proposed and how it is implemented within the proposed architecture has been explained. A few mathematical results about the architecture have been proposed, some of which are without proof.
Architecture Adaptive Computing Environment
NASA Technical Reports Server (NTRS)
Dorband, John E.
2006-01-01
Architecture Adaptive Computing Environment (aCe) is a software system that includes a language, compiler, and run-time library for parallel computing. aCe was developed to enable programmers to write programs, more easily than was previously possible, for a variety of parallel computing architectures. Heretofore, it has been perceived to be difficult to write parallel programs for parallel computers and more difficult to port the programs to different parallel computing architectures. In contrast, aCe is supportable on all high-performance computing architectures. Currently, it is supported on LINUX clusters. aCe uses parallel programming constructs that facilitate writing of parallel programs. Such constructs were used in single-instruction/multiple-data (SIMD) programming languages of the 1980s, including Parallel Pascal, Parallel Forth, C*, *LISP, and MasPar MPL. In aCe, these constructs are extended and implemented for both SIMD and multiple- instruction/multiple-data (MIMD) architectures. Two new constructs incorporated in aCe are those of (1) scalar and virtual variables and (2) pre-computed paths. The scalar-and-virtual-variables construct increases flexibility in optimizing memory utilization in various architectures. The pre-computed-paths construct enables the compiler to pre-compute part of a communication operation once, rather than computing it every time the communication operation is performed.
Supporting Undergraduate Computer Architecture Students Using a Visual MIPS64 CPU Simulator
ERIC Educational Resources Information Center
Patti, D.; Spadaccini, A.; Palesi, M.; Fazzino, F.; Catania, V.
2012-01-01
The topics of computer architecture are always taught using an Assembly dialect as an example. The most commonly used textbooks in this field use the MIPS64 Instruction Set Architecture (ISA) to help students in learning the fundamentals of computer architecture because of its orthogonality and its suitability for real-world applications. This…
Memristor-Based Computing Architecture: Design Methodologies and Circuit Techniques
2013-03-01
MEMRISTOR-BASED COMPUTING ARCHITECTURE : DESIGN METHODOLOGIES AND CIRCUIT TECHNIQUES POLYTECHNIC INSTITUTE OF NEW YORK UNIVERSITY...TECHNICAL REPORT 3. DATES COVERED (From - To) OCT 2010 – OCT 2012 4. TITLE AND SUBTITLE MEMRISTOR-BASED COMPUTING ARCHITECTURE : DESIGN METHODOLOGIES...schemes for a memristor-based reconfigurable architecture design have not been fully explored yet. Therefore, in this project, we investigated
Brain architecture: a design for natural computation.
Kaiser, Marcus
2007-12-15
Fifty years ago, John von Neumann compared the architecture of the brain with that of the computers he invented and which are still in use today. In those days, the organization of computers was based on concepts of brain organization. Here, we give an update on current results on the global organization of neural systems. For neural systems, we outline how the spatial and topological architecture of neuronal and cortical networks facilitates robustness against failures, fast processing and balanced network activation. Finally, we discuss mechanisms of self-organization for such architectures. After all, the organization of the brain might again inspire computer architecture.
A new software-based architecture for quantum computer
NASA Astrophysics Data System (ADS)
Wu, Nan; Song, FangMin; Li, Xiangdong
2010-04-01
In this paper, we study a reliable architecture of a quantum computer and a new instruction set and machine language for the architecture, which can improve the performance and reduce the cost of the quantum computing. We also try to address some key issues in detail in the software-driven universal quantum computers.
Architectures for single-chip image computing
NASA Astrophysics Data System (ADS)
Gove, Robert J.
1992-04-01
This paper will focus on the architectures of VLSI programmable processing components for image computing applications. TI, the maker of industry-leading RISC, DSP, and graphics components, has developed an architecture for a new-generation of image processors capable of implementing a plurality of image, graphics, video, and audio computing functions. We will show that the use of a single-chip heterogeneous MIMD parallel architecture best suits this class of processors--those which will dominate the desktop multimedia, document imaging, computer graphics, and visualization systems of this decade.
Transitioning ISR architecture into the cloud
NASA Astrophysics Data System (ADS)
Lash, Thomas D.
2012-06-01
Emerging cloud computing platforms offer an ideal opportunity for Intelligence, Surveillance, and Reconnaissance (ISR) intelligence analysis. Cloud computing platforms help overcome challenges and limitations of traditional ISR architectures. Modern ISR architectures can benefit from examining commercial cloud applications, especially as they relate to user experience, usage profiling, and transformational business models. This paper outlines legacy ISR architectures and their limitations, presents an overview of cloud technologies and their applications to the ISR intelligence mission, and presents an idealized ISR architecture implemented with cloud computing.
Architecture-Adaptive Computing Environment: A Tool for Teaching Parallel Programming
NASA Technical Reports Server (NTRS)
Dorband, John E.; Aburdene, Maurice F.
2002-01-01
Recently, networked and cluster computation have become very popular. This paper is an introduction to a new C based parallel language for architecture-adaptive programming, aCe C. The primary purpose of aCe (Architecture-adaptive Computing Environment) is to encourage programmers to implement applications on parallel architectures by providing them the assurance that future architectures will be able to run their applications with a minimum of modification. A secondary purpose is to encourage computer architects to develop new types of architectures by providing an easily implemented software development environment and a library of test applications. This new language should be an ideal tool to teach parallel programming. In this paper, we will focus on some fundamental features of aCe C.
Toward a Fault Tolerant Architecture for Vital Medical-Based Wearable Computing.
Abdali-Mohammadi, Fardin; Bajalan, Vahid; Fathi, Abdolhossein
2015-12-01
Advancements in computers and electronic technologies have led to the emergence of a new generation of efficient small intelligent systems. The products of such technologies might include Smartphones and wearable devices, which have attracted the attention of medical applications. These products are used less in critical medical applications because of their resource constraint and failure sensitivity. This is due to the fact that without safety considerations, small-integrated hardware will endanger patients' lives. Therefore, proposing some principals is required to construct wearable systems in healthcare so that the existing concerns are dealt with. Accordingly, this paper proposes an architecture for constructing wearable systems in critical medical applications. The proposed architecture is a three-tier one, supporting data flow from body sensors to cloud. The tiers of this architecture include wearable computers, mobile computing, and mobile cloud computing. One of the features of this architecture is its high possible fault tolerance due to the nature of its components. Moreover, the required protocols are presented to coordinate the components of this architecture. Finally, the reliability of this architecture is assessed by simulating the architecture and its components, and other aspects of the proposed architecture are discussed.
Advanced computer architecture specification for automated weld systems
NASA Technical Reports Server (NTRS)
Katsinis, Constantine
1994-01-01
This report describes the requirements for an advanced automated weld system and the associated computer architecture, and defines the overall system specification from a broad perspective. According to the requirements of welding procedures as they relate to an integrated multiaxis motion control and sensor architecture, the computer system requirements are developed based on a proven multiple-processor architecture with an expandable, distributed-memory, single global bus architecture, containing individual processors which are assigned to specific tasks that support sensor or control processes. The specified architecture is sufficiently flexible to integrate previously developed equipment, be upgradable and allow on-site modifications.
Quantum Computing Architectural Design
NASA Astrophysics Data System (ADS)
West, Jacob; Simms, Geoffrey; Gyure, Mark
2006-03-01
Large scale quantum computers will invariably require scalable architectures in addition to high fidelity gate operations. Quantum computing architectural design (QCAD) addresses the problems of actually implementing fault-tolerant algorithms given physical and architectural constraints beyond those of basic gate-level fidelity. Here we introduce a unified framework for QCAD that enables the scientist to study the impact of varying error correction schemes, architectural parameters including layout and scheduling, and physical operations native to a given architecture. Our software package, aptly named QCAD, provides compilation, manipulation/transformation, multi-paradigm simulation, and visualization tools. We demonstrate various features of the QCAD software package through several examples.
Recursive computer architecture for VLSI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Treleaven, P.C.; Hopkins, R.P.
1982-01-01
A general-purpose computer architecture based on the concept of recursion and suitable for VLSI computer systems built from replicated (lego-like) computing elements is presented. The recursive computer architecture is defined by presenting a program organisation, a machine organisation and an experimental machine implementation oriented to VLSI. The experimental implementation is being restricted to simple, identical microcomputers each containing a memory, a processor and a communications capability. This future generation of lego-like computer systems are termed fifth generation computers by the Japanese. 30 references.
Hypercluster Parallel Processor
NASA Technical Reports Server (NTRS)
Blech, Richard A.; Cole, Gary L.; Milner, Edward J.; Quealy, Angela
1992-01-01
Hypercluster computer system includes multiple digital processors, operation of which coordinated through specialized software. Configurable according to various parallel-computing architectures of shared-memory or distributed-memory class, including scalar computer, vector computer, reduced-instruction-set computer, and complex-instruction-set computer. Designed as flexible, relatively inexpensive system that provides single programming and operating environment within which one can investigate effects of various parallel-computing architectures and combinations on performance in solution of complicated problems like those of three-dimensional flows in turbomachines. Hypercluster software and architectural concepts are in public domain.
Distributed Computing Architecture for Image-Based Wavefront Sensing and 2 D FFTs
NASA Technical Reports Server (NTRS)
Smith, Jeffrey S.; Dean, Bruce H.; Haghani, Shadan
2006-01-01
Image-based wavefront sensing (WFS) provides significant advantages over interferometric-based wavefi-ont sensors such as optical design simplicity and stability. However, the image-based approach is computational intensive, and therefore, specialized high-performance computing architectures are required in applications utilizing the image-based approach. The development and testing of these high-performance computing architectures are essential to such missions as James Webb Space Telescope (JWST), Terrestial Planet Finder-Coronagraph (TPF-C and CorSpec), and Spherical Primary Optical Telescope (SPOT). The development of these specialized computing architectures require numerous two-dimensional Fourier Transforms, which necessitate an all-to-all communication when applied on a distributed computational architecture. Several solutions for distributed computing are presented with an emphasis on a 64 Node cluster of DSPs, multiple DSP FPGAs, and an application of low-diameter graph theory. Timing results and performance analysis will be presented. The solutions offered could be applied to other all-to-all communication and scientifically computationally complex problems.
Analysis OpenMP performance of AMD and Intel architecture for breaking waves simulation using MPS
NASA Astrophysics Data System (ADS)
Alamsyah, M. N. A.; Utomo, A.; Gunawan, P. H.
2018-03-01
Simulation of breaking waves by using Navier-Stokes equation via moving particle semi-implicit method (MPS) over close domain is given. The results show the parallel computing on multicore architecture using OpenMP platform can reduce the computational time almost half of the serial time. Here, the comparison using two computer architectures (AMD and Intel) are performed. The results using Intel architecture is shown better than AMD architecture in CPU time. However, in efficiency, the computer with AMD architecture gives slightly higher than the Intel. For the simulation by 1512 number of particles, the CPU time using Intel and AMD are 12662.47 and 28282.30 respectively. Moreover, the efficiency using similar number of particles, AMD obtains 50.09 % and Intel up to 49.42 %.
A synchronized computational architecture for generalized bilateral control of robot arms
NASA Technical Reports Server (NTRS)
Bejczy, Antal K.; Szakaly, Zoltan
1987-01-01
This paper describes a computational architecture for an interconnected high speed distributed computing system for generalized bilateral control of robot arms. The key method of the architecture is the use of fully synchronized, interrupt driven software. Since an objective of the development is to utilize the processing resources efficiently, the synchronization is done in the hardware level to reduce system software overhead. The architecture also achieves a balaced load on the communication channel. The paper also describes some architectural relations to trading or sharing manual and automatic control.
Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation
NASA Technical Reports Server (NTRS)
Stocker, John C.; Golomb, Andrew M.
2011-01-01
Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.
Architectural Specialization for Inter-Iteration Loop Dependence Patterns
2015-10-01
Architectural Specialization for Inter-Iteration Loop Dependence Patterns Christopher Batten Computer Systems Laboratory School of Electrical and...Trends in Computer Architecture Transistors (Thousands) Frequency (MHz) Typical Power (W) MIPS R2K Intel P4 DEC Alpha 21264 Data collected by M...T as ks p er Jo ule ) Simple Processor Design Power Constraint High-Performance Architectures Embedded Architectures Design Performance
Manyscale Computing for Sensor Processing in Support of Space Situational Awareness
NASA Astrophysics Data System (ADS)
Schmalz, M.; Chapman, W.; Hayden, E.; Sahni, S.; Ranka, S.
2014-09-01
Increasing image and signal data burden associated with sensor data processing in support of space situational awareness implies continuing computational throughput growth beyond the petascale regime. In addition to growing applications data burden and diversity, the breadth, diversity and scalability of high performance computing architectures and their various organizations challenge the development of a single, unifying, practicable model of parallel computation. Therefore, models for scalable parallel processing have exploited architectural and structural idiosyncrasies, yielding potential misapplications when legacy programs are ported among such architectures. In response to this challenge, we have developed a concise, efficient computational paradigm and software called Manyscale Computing to facilitate efficient mapping of annotated application codes to heterogeneous parallel architectures. Our theory, algorithms, software, and experimental results support partitioning and scheduling of application codes for envisioned parallel architectures, in terms of work atoms that are mapped (for example) to threads or thread blocks on computational hardware. Because of the rigor, completeness, conciseness, and layered design of our manyscale approach, application-to-architecture mapping is feasible and scalable for architectures at petascales, exascales, and above. Further, our methodology is simple, relying primarily on a small set of primitive mapping operations and support routines that are readily implemented on modern parallel processors such as graphics processing units (GPUs) and hybrid multi-processors (HMPs). In this paper, we overview the opportunities and challenges of manyscale computing for image and signal processing in support of space situational awareness applications. We discuss applications in terms of a layered hardware architecture (laboratory > supercomputer > rack > processor > component hierarchy). Demonstration applications include performance analysis and results in terms of execution time as well as storage, power, and energy consumption for bus-connected and/or networked architectures. The feasibility of the manyscale paradigm is demonstrated by addressing four principal challenges: (1) architectural/structural diversity, parallelism, and locality, (2) masking of I/O and memory latencies, (3) scalability of design as well as implementation, and (4) efficient representation/expression of parallel applications. Examples will demonstrate how manyscale computing helps solve these challenges efficiently on real-world computing systems.
NASA Astrophysics Data System (ADS)
Jiang, Yuning; Kang, Jinfeng; Wang, Xinan
2017-03-01
Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.
Cognitive Architectures and Human-Computer Interaction. Introduction to Special Issue.
ERIC Educational Resources Information Center
Gray, Wayne D.; Young, Richard M.; Kirschenbaum, Susan S.
1997-01-01
In this introduction to a special issue on cognitive architectures and human-computer interaction (HCI), editors and contributors provide a brief overview of cognitive architectures. The following four architectures represented by articles in this issue are: Soar; LICAI (linked model of comprehension-based action planning and instruction taking);…
Biomimetic design processes in architecture: morphogenetic and evolutionary computational design.
Menges, Achim
2012-03-01
Design computation has profound impact on architectural design methods. This paper explains how computational design enables the development of biomimetic design processes specific to architecture, and how they need to be significantly different from established biomimetic processes in engineering disciplines. The paper first explains the fundamental difference between computer-aided and computational design in architecture, as the understanding of this distinction is of critical importance for the research presented. Thereafter, the conceptual relation and possible transfer of principles from natural morphogenesis to design computation are introduced and the related developments of generative, feature-based, constraint-based, process-based and feedback-based computational design methods are presented. This morphogenetic design research is then related to exploratory evolutionary computation, followed by the presentation of two case studies focusing on the exemplary development of spatial envelope morphologies and urban block morphologies.
The flight telerobotic servicer: From functional architecture to computer architecture
NASA Technical Reports Server (NTRS)
Lumia, Ronald; Fiala, John
1989-01-01
After a brief tutorial on the NASA/National Bureau of Standards Standard Reference Model for Telerobot Control System Architecture (NASREM) functional architecture, the approach to its implementation is shown. First, interfaces must be defined which are capable of supporting the known algorithms. This is illustrated by considering the interfaces required for the SERVO level of the NASREM functional architecture. After interface definition, the specific computer architecture for the implementation must be determined. This choice is obviously technology dependent. An example illustrating one possible mapping of the NASREM functional architecture to a particular set of computers which implements it is shown. The result of choosing the NASREM functional architecture is that it provides a technology independent paradigm which can be mapped into a technology dependent implementation capable of evolving with technology in the laboratory and in space.
Innovative architectures for dense multi-microprocessor computers
NASA Technical Reports Server (NTRS)
Donaldson, Thomas; Doty, Karl; Engle, Steven W.; Larson, Robert E.; O'Reilly, John G.
1988-01-01
The results of a Phase I Small Business Innovative Research (SBIR) project performed for the NASA Langley Computational Structural Mechanics Group are described. The project resulted in the identification of a family of chordal-ring interconnection architectures with excellent potential to serve as the basis for new multimicroprocessor (MMP) computers. The paper presents examples of how computational algorithms from structural mechanics can be efficiently implemented on the chordal-ring architecture.
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1992-01-01
The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
An Object Oriented Extensible Architecture for Affordable Aerospace Propulsion Systems
NASA Technical Reports Server (NTRS)
Follen, Gregory J.; Lytle, John K. (Technical Monitor)
2002-01-01
Driven by a need to explore and develop propulsion systems that exceeded current computing capabilities, NASA Glenn embarked on a novel strategy leading to the development of an architecture that enables propulsion simulations never thought possible before. Full engine 3 Dimensional Computational Fluid Dynamic propulsion system simulations were deemed impossible due to the impracticality of the hardware and software computing systems required. However, with a software paradigm shift and an embracing of parallel and distributed processing, an architecture was designed to meet the needs of future propulsion system modeling. The author suggests that the architecture designed at the NASA Glenn Research Center for propulsion system modeling has potential for impacting the direction of development of affordable weapons systems currently under consideration by the Applied Vehicle Technology Panel (AVT). This paper discusses the salient features of the NPSS Architecture including its interface layer, object layer, implementation for accessing legacy codes, numerical zooming infrastructure and its computing layer. The computing layer focuses on the use and deployment of these propulsion simulations on parallel and distributed computing platforms which has been the focus of NASA Ames. Additional features of the object oriented architecture that support MultiDisciplinary (MD) Coupling, computer aided design (CAD) access and MD coupling objects will be discussed. Included will be a discussion of the successes, challenges and benefits of implementing this architecture.
Distributed computing environments for future space control systems
NASA Technical Reports Server (NTRS)
Viallefont, Pierre
1993-01-01
The aim of this paper is to present the results of a CNES research project on distributed computing systems. The purpose of this research was to study the impact of the use of new computer technologies in the design and development of future space applications. The first part of this study was a state-of-the-art review of distributed computing systems. One of the interesting ideas arising from this review is the concept of a 'virtual computer' allowing the distributed hardware architecture to be hidden from a software application. The 'virtual computer' can improve system performance by adapting the best architecture (addition of computers) to the software application without having to modify its source code. This concept can also decrease the cost and obsolescence of the hardware architecture. In order to verify the feasibility of the 'virtual computer' concept, a prototype representative of a distributed space application is being developed independently of the hardware architecture.
Electro-Optic Computing Architectures. Volume I
1998-02-01
The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit (OW
Image-Processing Software For A Hypercube Computer
NASA Technical Reports Server (NTRS)
Lee, Meemong; Mazer, Alan S.; Groom, Steven L.; Williams, Winifred I.
1992-01-01
Concurrent Image Processing Executive (CIPE) is software system intended to develop and use image-processing application programs on concurrent computing environment. Designed to shield programmer from complexities of concurrent-system architecture, it provides interactive image-processing environment for end user. CIPE utilizes architectural characteristics of particular concurrent system to maximize efficiency while preserving architectural independence from user and programmer. CIPE runs on Mark-IIIfp 8-node hypercube computer and associated SUN-4 host computer.
Experimental Comparison of Two Quantum Computing Architectures
2017-03-28
IN A U G U RA L A RT IC LE CO M PU TE R SC IE N CE S Experimental comparison of two quantum computing architectures Norbert M. Linkea,b,1, Dmitri...the vast computing power a universal quantumcomputer could offer, several candidate systems are being explored. They have allowed experimental ...existing systems and the role of architecture in quantum computer design . These will be crucial for the realization of more advanced future incarna
A learnable parallel processing architecture towards unity of memory and computing
NASA Astrophysics Data System (ADS)
Li, H.; Gao, B.; Chen, Z.; Zhao, Y.; Huang, P.; Ye, H.; Liu, L.; Liu, X.; Kang, J.
2015-08-01
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named “iMemComp”, where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped “iMemComp” with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on “iMemComp” can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.
A learnable parallel processing architecture towards unity of memory and computing.
Li, H; Gao, B; Chen, Z; Zhao, Y; Huang, P; Ye, H; Liu, L; Liu, X; Kang, J
2015-08-14
Developing energy-efficient parallel information processing systems beyond von Neumann architecture is a long-standing goal of modern information technologies. The widely used von Neumann computer architecture separates memory and computing units, which leads to energy-hungry data movement when computers work. In order to meet the need of efficient information processing for the data-driven applications such as big data and Internet of Things, an energy-efficient processing architecture beyond von Neumann is critical for the information society. Here we show a non-von Neumann architecture built of resistive switching (RS) devices named "iMemComp", where memory and logic are unified with single-type devices. Leveraging nonvolatile nature and structural parallelism of crossbar RS arrays, we have equipped "iMemComp" with capabilities of computing in parallel and learning user-defined logic functions for large-scale information processing tasks. Such architecture eliminates the energy-hungry data movement in von Neumann computers. Compared with contemporary silicon technology, adder circuits based on "iMemComp" can improve the speed by 76.8% and the power dissipation by 60.3%, together with a 700 times aggressive reduction in the circuit area.
Digital optical computers at the optoelectronic computing systems center
NASA Technical Reports Server (NTRS)
Jordan, Harry F.
1991-01-01
The Digital Optical Computing Program within the National Science Foundation Engineering Research Center for Opto-electronic Computing Systems has as its specific goal research on optical computing architectures suitable for use at the highest possible speeds. The program can be targeted toward exploiting the time domain because other programs in the Center are pursuing research on parallel optical systems, exploiting optical interconnection and optical devices and materials. Using a general purpose computing architecture as the focus, we are developing design techniques, tools and architecture for operation at the speed of light limit. Experimental work is being done with the somewhat low speed components currently available but with architectures which will scale up in speed as faster devices are developed. The design algorithms and tools developed for a general purpose, stored program computer are being applied to other systems such as optimally controlled optical communication networks.
Resource Efficient Hardware Architecture for Fast Computation of Running Max/Min Filters
Torres-Huitzil, Cesar
2013-01-01
Running max/min filters on rectangular kernels are widely used in many digital signal and image processing applications. Filtering with a k × k kernel requires of k 2 − 1 comparisons per sample for a direct implementation; thus, performance scales expensively with the kernel size k. Faster computations can be achieved by kernel decomposition and using constant time one-dimensional algorithms on custom hardware. This paper presents a hardware architecture for real-time computation of running max/min filters based on the van Herk/Gil-Werman (HGW) algorithm. The proposed architecture design uses less computation and memory resources than previously reported architectures when targeted to Field Programmable Gate Array (FPGA) devices. Implementation results show that the architecture is able to compute max/min filters, on 1024 × 1024 images with up to 255 × 255 kernels, in around 8.4 milliseconds, 120 frames per second, at a clock frequency of 250 MHz. The implementation is highly scalable for the kernel size with good performance/area tradeoff suitable for embedded applications. The applicability of the architecture is shown for local adaptive image thresholding. PMID:24288456
Electro-Optic Computing Architectures: Volume II. Components and System Design and Analysis
1998-02-01
The objective of the Electro - Optic Computing Architecture (EOCA) program was to develop multi-function electro - optic interfaces and optical...interconnect units to enhance the performance of parallel processor systems and form the building blocks for future electro - optic computing architectures...Specifically, three multi-function interface modules were targeted for development - an Electro - Optic Interface (EOI), an Optical Interconnection Unit
NASA Astrophysics Data System (ADS)
Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng
2018-04-01
In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.
NASA Technical Reports Server (NTRS)
Hsia, T. C.; Lu, G. Z.; Han, W. H.
1987-01-01
In advanced robot control problems, on-line computation of inverse Jacobian solution is frequently required. Parallel processing architecture is an effective way to reduce computation time. A parallel processing architecture is developed for the inverse Jacobian (inverse differential kinematic equation) of the PUMA arm. The proposed pipeline/parallel algorithm can be inplemented on an IC chip using systolic linear arrays. This implementation requires 27 processing cells and 25 time units. Computation time is thus significantly reduced.
Pyramidal neurovision architecture for vision machines
NASA Astrophysics Data System (ADS)
Gupta, Madan M.; Knopf, George K.
1993-08-01
The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.
Collaborative Working Architecture for IoT-Based Applications.
Mora, Higinio; Signes-Pont, María Teresa; Gil, David; Johnsson, Magnus
2018-05-23
The new sensing applications need enhanced computing capabilities to handle the requirements of complex and huge data processing. The Internet of Things (IoT) concept brings processing and communication features to devices. In addition, the Cloud Computing paradigm provides resources and infrastructures for performing the computations and outsourcing the work from the IoT devices. This scenario opens new opportunities for designing advanced IoT-based applications, however, there is still much research to be done to properly gear all the systems for working together. This work proposes a collaborative model and an architecture to take advantage of the available computing resources. The resulting architecture involves a novel network design with different levels which combines sensing and processing capabilities based on the Mobile Cloud Computing (MCC) paradigm. An experiment is included to demonstrate that this approach can be used in diverse real applications. The results show the flexibility of the architecture to perform complex computational tasks of advanced applications.
Optimizing Engineering Tools Using Modern Ground Architectures
2017-12-01
Considerations,” International Journal of Computer Science & Engineering Survey , vol. 5, no. 4, 2014. [10] R. Bell. (n.d). A beginner’s guide to big O notation...scientific community. Traditional computing architectures were not capable of processing the data efficiently, or in some cases, could not process the...thesis investigates how these modern computing architectures could be leveraged by industry and academia to improve the performance and capabilities of
Architecture independent environment for developing engineering software on MIMD computers
NASA Technical Reports Server (NTRS)
Valimohamed, Karim A.; Lopez, L. A.
1990-01-01
Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management.
Computer vision camera with embedded FPGA processing
NASA Astrophysics Data System (ADS)
Lecerf, Antoine; Ouellet, Denis; Arias-Estrada, Miguel
2000-03-01
Traditional computer vision is based on a camera-computer system in which the image understanding algorithms are embedded in the computer. To circumvent the computational load of vision algorithms, low-level processing and imaging hardware can be integrated in a single compact module where a dedicated architecture is implemented. This paper presents a Computer Vision Camera based on an open architecture implemented in an FPGA. The system is targeted to real-time computer vision tasks where low level processing and feature extraction tasks can be implemented in the FPGA device. The camera integrates a CMOS image sensor, an FPGA device, two memory banks, and an embedded PC for communication and control tasks. The FPGA device is a medium size one equivalent to 25,000 logic gates. The device is connected to two high speed memory banks, an IS interface, and an imager interface. The camera can be accessed for architecture programming, data transfer, and control through an Ethernet link from a remote computer. A hardware architecture can be defined in a Hardware Description Language (like VHDL), simulated and synthesized into digital structures that can be programmed into the FPGA and tested on the camera. The architecture of a classical multi-scale edge detection algorithm based on a Laplacian of Gaussian convolution has been developed to show the capabilities of the system.
State-of-the-art in Heterogeneous Computing
Brodtkorb, Andre R.; Dyken, Christopher; Hagen, Trond R.; ...
2010-01-01
Node level heterogeneous architectures have become attractive during the last decade for several reasons: compared to traditional symmetric CPUs, they offer high peak performance and are energy and/or cost efficient. With the increase of fine-grained parallelism in high-performance computing, as well as the introduction of parallelism in workstations, there is an acute need for a good overview and understanding of these architectures. We give an overview of the state-of-the-art in heterogeneous computing, focusing on three commonly found architectures: the Cell Broadband Engine Architecture, graphics processing units (GPUs), and field programmable gate arrays (FPGAs). We present a review of hardware, availablemore » software tools, and an overview of state-of-the-art techniques and algorithms. Furthermore, we present a qualitative and quantitative comparison of the architectures, and give our view on the future of heterogeneous computing.« less
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1991-01-01
The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
Advanced computer architecture for large-scale real-time applications.
DOT National Transportation Integrated Search
1973-04-01
Air traffic control automation is identified as a crucial problem which provides a complex, real-time computer application environment. A novel computer architecture in the form of a pipeline associative processor is conceived to achieve greater perf...
Integrating Computing Resources: A Shared Distributed Architecture for Academics and Administrators.
ERIC Educational Resources Information Center
Beltrametti, Monica; English, Will
1994-01-01
Development and implementation of a shared distributed computing architecture at the University of Alberta (Canada) are described. Aspects discussed include design of the architecture, users' views of the electronic environment, technical and managerial challenges, and the campuswide human infrastructures needed to manage such an integrated…
ERIC Educational Resources Information Center
Farid, Ayman A.; Zaghloul, Weaam M.; Dewidar, Khaled M.
2014-01-01
The great shift in sustainability and computer aided design in the field of architecture caused a remarkable change in the architecture philosophy, new aspects of beauty and aesthetic values are being introduced, and traditional definitions for beauty cannot fully cover this aspects, which causes a gap between; new architecture works criticism and…
Programmable hardware for reconfigurable computing systems
NASA Astrophysics Data System (ADS)
Smith, Stephen
1996-10-01
In 1945 the work of J. von Neumann and H. Goldstein created the principal architecture for electronic computation that has now lasted fifty years. Nevertheless alternative architectures have been created that have computational capability, for special tasks, far beyond that feasible with von Neumann machines. The emergence of high capacity programmable logic devices has made the realization of these architectures practical. The original ENIAC and EDVAC machines were conceived to solve special mathematical problems that were far from today's concept of 'killer applications.' In a similar vein programmable hardware computation is being used today to solve unique mathematical problems. Our programmable hardware activity is focused on the research and development of novel computational systems based upon the reconfigurability of our programmable logic devices. We explore our programmable logic architectures and their implications for programmable hardware. One programmable hardware board implementation is detailed.
Execution environment for intelligent real-time control systems
NASA Technical Reports Server (NTRS)
Sztipanovits, Janos
1987-01-01
Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment.
Efficient Phase Unwrapping Architecture for Digital Holographic Microscopy
Hwang, Wen-Jyi; Cheng, Shih-Chang; Cheng, Chau-Jern
2011-01-01
This paper presents a novel phase unwrapping architecture for accelerating the computational speed of digital holographic microscopy (DHM). A fast Fourier transform (FFT) based phase unwrapping algorithm providing a minimum squared error solution is adopted for hardware implementation because of its simplicity and robustness to noise. The proposed architecture is realized in a pipeline fashion to maximize throughput of the computation. Moreover, the number of hardware multipliers and dividers are minimized to reduce the hardware costs. The proposed architecture is used as a custom user logic in a system on programmable chip (SOPC) for physical performance measurement. Experimental results reveal that the proposed architecture is effective for expediting the computational speed while consuming low hardware resources for designing an embedded DHM system. PMID:22163688
ERIC Educational Resources Information Center
Betts, Janelle Lyon
2001-01-01
Describes a high school art assignment in which students utilize Appleworks or Claris Works to design their own house, after learning about architectural styles and how to use the computer program. States that the project develops student computer skills and increases student knowledge about architecture. (CMK)
Evaluation of Visual Computer Simulator for Computer Architecture Education
ERIC Educational Resources Information Center
Imai, Yoshiro; Imai, Masatoshi; Moritoh, Yoshio
2013-01-01
This paper presents trial evaluation of a visual computer simulator in 2009-2011, which has been developed to play some roles of both instruction facility and learning tool simultaneously. And it illustrates an example of Computer Architecture education for University students and usage of e-Learning tool for Assembly Programming in order to…
Design of a massively parallel computer using bit serial processing elements
NASA Technical Reports Server (NTRS)
Aburdene, Maurice F.; Khouri, Kamal S.; Piatt, Jason E.; Zheng, Jianqing
1995-01-01
A 1-bit serial processor designed for a parallel computer architecture is described. This processor is used to develop a massively parallel computational engine, with a single instruction-multiple data (SIMD) architecture. The computer is simulated and tested to verify its operation and to measure its performance for further development.
A heterogeneous hierarchical architecture for real-time computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Skroch, D.A.; Fornaro, R.J.
The need for high-speed data acquisition and control algorithms has prompted continued research in the area of multiprocessor systems and related programming techniques. The result presented here is a unique hardware and software architecture for high-speed real-time computer systems. The implementation of a prototype of this architecture has required the integration of architecture, operating systems and programming languages into a cohesive unit. This report describes a Heterogeneous Hierarchial Architecture for Real-Time (H{sup 2} ART) and system software for program loading and interprocessor communication.
Three Program Architecture for Design Optimization
NASA Technical Reports Server (NTRS)
Miura, Hirokazu; Olson, Lawrence E. (Technical Monitor)
1998-01-01
In this presentation, I would like to review historical perspective on the program architecture used to build design optimization capabilities based on mathematical programming and other numerical search techniques. It is rather straightforward to classify the program architecture in three categories as shown above. However, the relative importance of each of the three approaches has not been static, instead dynamically changing as the capabilities of available computational resource increases. For example, we considered that the direct coupling architecture would never be used for practical problems, but availability of such computer systems as multi-processor. In this presentation, I would like to review the roles of three architecture from historical as well as current and future perspective. There may also be some possibility for emergence of hybrid architecture. I hope to provide some seeds for active discussion where we are heading to in the very dynamic environment for high speed computing and communication.
ERIC Educational Resources Information Center
Arumi, Francisco N.
Computer programs capable of describing the thermal behavior of buildings are used to help architectural students understand environmental systems. The Numerical Simulation Laboratory at the Architectural School of the University of Texas at Austin was developed to provide the necessary software capable of simulating the energy transactions…
NASA Astrophysics Data System (ADS)
Mills, R. T.; Rupp, K.; Smith, B. F.; Brown, J.; Knepley, M.; Zhang, H.; Adams, M.; Hammond, G. E.
2017-12-01
As the high-performance computing community pushes towards the exascale horizon, power and heat considerations have driven the increasing importance and prevalence of fine-grained parallelism in new computer architectures. High-performance computing centers have become increasingly reliant on GPGPU accelerators and "manycore" processors such as the Intel Xeon Phi line, and 512-bit SIMD registers have even been introduced in the latest generation of Intel's mainstream Xeon server processors. The high degree of fine-grained parallelism and more complicated memory hierarchy considerations of such "manycore" processors present several challenges to existing scientific software. Here, we consider how the massively parallel, open-source hydrologic flow and reactive transport code PFLOTRAN - and the underlying Portable, Extensible Toolkit for Scientific Computation (PETSc) library on which it is built - can best take advantage of such architectures. We will discuss some key features of these novel architectures and our code optimizations and algorithmic developments targeted at them, and present experiences drawn from working with a wide range of PFLOTRAN benchmark problems on these architectures.
NASA Technical Reports Server (NTRS)
Weeks, Cindy Lou
1986-01-01
Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Potok, Thomas; Schuman, Catherine; Patton, Robert
The White House and Department of Energy have been instrumental in driving the development of a neuromorphic computing program to help the United States continue its lead in basic research into (1) Beyond Exascale—high performance computing beyond Moore’s Law and von Neumann architectures, (2) Scientific Discovery—new paradigms for understanding increasingly large and complex scientific data, and (3) Emerging Architectures—assessing the potential of neuromorphic and quantum architectures. Neuromorphic computing spans a broad range of scientific disciplines from materials science to devices, to computer science, to neuroscience, all of which are required to solve the neuromorphic computing grand challenge. In our workshopmore » we focus on the computer science aspects, specifically from a neuromorphic device through an application. Neuromorphic devices present a very different paradigm to the computer science community from traditional von Neumann architectures, which raises six major questions about building a neuromorphic application from the device level. We used these fundamental questions to organize the workshop program and to direct the workshop panels and discussions. From the white papers, presentations, panels, and discussions, there emerged several recommendations on how to proceed.« less
Neuromorphic Computing – From Materials Research to Systems Architecture Roundtable
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schuller, Ivan K.; Stevens, Rick; Pino, Robinson
2015-10-29
Computation in its many forms is the engine that fuels our modern civilization. Modern computation—based on the von Neumann architecture—has allowed, until now, the development of continuous improvements, as predicted by Moore’s law. However, computation using current architectures and materials will inevitably—within the next 10 years—reach a limit because of fundamental scientific reasons. DOE convened a roundtable of experts in neuromorphic computing systems, materials science, and computer science in Washington on October 29-30, 2015 to address the following basic questions: Can brain-like (“neuromorphic”) computing devices based on new material concepts and systems be developed to dramatically outperform conventional CMOS basedmore » technology? If so, what are the basic research challenges for materials sicence and computing? The overarching answer that emerged was: The development of novel functional materials and devices incorporated into unique architectures will allow a revolutionary technological leap toward the implementation of a fully “neuromorphic” computer. To address this challenge, the following issues were considered: The main differences between neuromorphic and conventional computing as related to: signaling models, timing/clock, non-volatile memory, architecture, fault tolerance, integrated memory and compute, noise tolerance, analog vs. digital, and in situ learning New neuromorphic architectures needed to: produce lower energy consumption, potential novel nanostructured materials, and enhanced computation Device and materials properties needed to implement functions such as: hysteresis, stability, and fault tolerance Comparisons of different implementations: spin torque, memristors, resistive switching, phase change, and optical schemes for enhanced breakthroughs in performance, cost, fault tolerance, and/or manufacturability.« less
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Potok, Thomas E; Schuman, Catherine D; Young, Steven R
Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are intractable to train on current systems. Building the topologies of the deep learning network requires hand tuning, and implementing the network in hardware is expensive in both cost and power. In this paper, we evaluate deep learning models using three different computing architectures to address these problems: quantum computing to train complex topologies, high performance computing (HPC) to automatically determinemore » network topology, and neuromorphic computing for a low-power hardware implementation. Due to input size limitations of current quantum computers we use the MNIST dataset for our evaluation. The results show the possibility of using the three architectures in tandem to explore complex deep learning networks that are untrainable using a von Neumann architecture. We show that a quantum computer can find high quality values of intra-layer connections and weights, while yielding a tractable time result as the complexity of the network increases; a high performance computer can find optimal layer-based topologies; and a neuromorphic computer can represent the complex topology and weights derived from the other architectures in low power memristive hardware. This represents a new capability that is not feasible with current von Neumann architecture. It potentially enables the ability to solve very complicated problems unsolvable with current computing technologies.« less
ERIC Educational Resources Information Center
Amenyo, John-Thones
2012-01-01
Carefully engineered playable games can serve as vehicles for students and practitioners to learn and explore the programming of advanced computer architectures to execute applications, such as high performance computing (HPC) and complex, inter-networked, distributed systems. The article presents families of playable games that are grounded in…
Gschwind, Michael K
2013-04-16
Mechanisms for generating and executing programs for a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA) are provided. A computer program product comprising a computer recordable medium having a computer readable program recorded thereon is provided. The computer readable program, when executed on a computing device, causes the computing device to receive one or more instructions and execute the one or more instructions using logic in an execution unit of the computing device. The logic implements a floating point (FP) only single instruction multiple data (SIMD) instruction set architecture (ISA), based on data stored in a vector register file of the computing device. The vector register file is configured to store both scalar and floating point values as vectors having a plurality of vector elements.
NASA Technical Reports Server (NTRS)
Denning, Peter J.; Tichy, Walter F.
1990-01-01
Highly parallel computing architectures are the only means to achieve the computation rates demanded by advanced scientific problems. A decade of research has demonstrated the feasibility of such machines and current research focuses on which architectures designated as multiple instruction multiple datastream (MIMD) and single instruction multiple datastream (SIMD) have produced the best results to date; neither shows a decisive advantage for most near-homogeneous scientific problems. For scientific problems with many dissimilar parts, more speculative architectures such as neural networks or data flow may be needed.
Switching from computer to microcomputer architecture education
NASA Astrophysics Data System (ADS)
Bolanakis, Dimosthenis E.; Kotsis, Konstantinos T.; Laopoulos, Theodore
2010-03-01
In the last decades, the technological and scientific evolution of the computing discipline has been widely affecting research in software engineering education, which nowadays advocates more enlightened and liberal ideas. This article reviews cross-disciplinary research on a computer architecture class in consideration of its switching to microcomputer architecture. The authors present their strategies towards a successful crossing of boundaries between engineering disciplines. This communication aims at providing a different aspect on professional courses that are, nowadays, addressed at the expense of traditional courses.
Three-Dimensional Nanobiocomputing Architectures With Neuronal Hypercells
2007-06-01
Neumann architectures, and CMOS fabrication. Novel solutions of massive parallel distributed computing and processing (pipelined due to systolic... and processing platforms utilizing molecular hardware within an enabling organization and architecture. The design technology is based on utilizing a...Microsystems and Nanotechnologies investigated a novel 3D3 (Hardware Software Nanotechnology) technology to design super-high performance computing
Switching from Computer to Microcomputer Architecture Education
ERIC Educational Resources Information Center
Bolanakis, Dimosthenis E.; Kotsis, Konstantinos T.; Laopoulos, Theodore
2010-01-01
In the last decades, the technological and scientific evolution of the computing discipline has been widely affecting research in software engineering education, which nowadays advocates more enlightened and liberal ideas. This article reviews cross-disciplinary research on a computer architecture class in consideration of its switching to…
An Architecture for Cross-Cloud System Management
NASA Astrophysics Data System (ADS)
Dodda, Ravi Teja; Smith, Chris; van Moorsel, Aad
The emergence of the cloud computing paradigm promises flexibility and adaptability through on-demand provisioning of compute resources. As the utilization of cloud resources extends beyond a single provider, for business as well as technical reasons, the issue of effectively managing such resources comes to the fore. Different providers expose different interfaces to their compute resources utilizing varied architectures and implementation technologies. This heterogeneity poses a significant system management problem, and can limit the extent to which the benefits of cross-cloud resource utilization can be realized. We address this problem through the definition of an architecture to facilitate the management of compute resources from different cloud providers in an homogenous manner. This preserves the flexibility and adaptability promised by the cloud computing paradigm, whilst enabling the benefits of cross-cloud resource utilization to be realized. The practical efficacy of the architecture is demonstrated through an implementation utilizing compute resources managed through different interfaces on the Amazon Elastic Compute Cloud (EC2) service. Additionally, we provide empirical results highlighting the performance differential of these different interfaces, and discuss the impact of this performance differential on efficiency and profitability.
A Low Cost VLSI Architecture for Spike Sorting Based on Feature Extraction with Peak Search.
Chang, Yuan-Jyun; Hwang, Wen-Jyi; Chen, Chih-Chang
2016-12-07
The goal of this paper is to present a novel VLSI architecture for spike sorting with high classification accuracy, low area costs and low power consumption. A novel feature extraction algorithm with low computational complexities is proposed for the design of the architecture. In the feature extraction algorithm, a spike is separated into two portions based on its peak value. The area of each portion is then used as a feature. The algorithm is simple to implement and less susceptible to noise interference. Based on the algorithm, a novel architecture capable of identifying peak values and computing spike areas concurrently is proposed. To further accelerate the computation, a spike can be divided into a number of segments for the local feature computation. The local features are subsequently merged with the global ones by a simple hardware circuit. The architecture can also be easily operated in conjunction with the circuits for commonly-used spike detection algorithms, such as the Non-linear Energy Operator (NEO). The architecture has been implemented by an Application-Specific Integrated Circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture is well suited for real-time multi-channel spike detection and feature extraction requiring low hardware area costs, low power consumption and high classification accuracy.
Generic Divide and Conquer Internet-Based Computing
NASA Technical Reports Server (NTRS)
Radenski, Atanas; Follen, Gregory J. (Technical Monitor)
2001-01-01
The rapid growth of internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of new, internet-oriented software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high -performance computing applications community. The general goal of this research project is to contribute to better understanding of the transition to internet-based high -performance computing and to develop solutions for some of the difficulties of this transition. More specifically, our goal is to design an architecture for generic divide and conquer internet-based computing, to develop a portable implementation of this architecture, to create an example library of high-performance divide-and-conquer computing agents that run on top of this architecture, and to evaluate the performance of these agents. We have been designing an architecture that incorporates a master task-pool server and utilizes satellite computational servers that operate on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. Our designed architecture is intended to be complementary to and accessible from computational grids such as Globus, Legion, and Condor. Grids provide remote access to existing high-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end internet nodes. Our project is focused on a generic divide-and-conquer paradigm and its applications that operate on a loose and ever changing pool of lower-end internet nodes.
THE COMPUTER AND THE ARCHITECTURAL PROFESSION.
ERIC Educational Resources Information Center
HAVILAND, DAVID S.
THE ROLE OF ADVANCING TECHNOLOGY IN THE FIELD OF ARCHITECTURE IS DISCUSSED IN THIS REPORT. PROBLEMS IN COMMUNICATION AND THE DESIGN PROCESS ARE IDENTIFIED. ADVANTAGES AND DISADVANTAGES OF COMPUTERS ARE MENTIONED IN RELATION TO MAN AND MACHINE INTERACTION. PRESENT AND FUTURE IMPLICATIONS OF COMPUTER USAGE ARE IDENTIFIED AND DISCUSSED WITH RESPECT…
The Contribution of Visualization to Learning Computer Architecture
ERIC Educational Resources Information Center
Yehezkel, Cecile; Ben-Ari, Mordechai; Dreyfus, Tommy
2007-01-01
This paper describes a visualization environment and associated learning activities designed to improve learning of computer architecture. The environment, EasyCPU, displays a model of the components of a computer and the dynamic processes involved in program execution. We present the results of a research program that analysed the contribution of…
Technology advances and market forces: Their impact on high performance architectures
NASA Technical Reports Server (NTRS)
Best, D. R.
1978-01-01
Reasonable projections into future supercomputer architectures and technology require an analysis of the computer industry market environment, the current capabilities and trends within the component industry, and the research activities on computer architecture in the industrial and academic communities. Management, programmer, architect, and user must cooperate to increase the efficiency of supercomputer development efforts. Care must be taken to match the funding, compiler, architecture and application with greater attention to testability, maintainability, reliability, and usability than supercomputer development programs of the past.
A Case Study on Neural Inspired Dynamic Memory Management Strategies for High Performance Computing.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vineyard, Craig Michael; Verzi, Stephen Joseph
As high performance computing architectures pursue more computational power there is a need for increased memory capacity and bandwidth as well. A multi-level memory (MLM) architecture addresses this need by combining multiple memory types with different characteristics as varying levels of the same architecture. How to efficiently utilize this memory infrastructure is an unknown challenge, and in this research we sought to investigate whether neural inspired approaches can meaningfully help with memory management. In particular we explored neurogenesis inspired re- source allocation, and were able to show a neural inspired mixed controller policy can beneficially impact how MLM architectures utilizemore » memory.« less
Computing architecture for autonomous microgrids
Goldsmith, Steven Y.
2015-09-29
A computing architecture that facilitates autonomously controlling operations of a microgrid is described herein. A microgrid network includes numerous computing devices that execute intelligent agents, each of which is assigned to a particular entity (load, source, storage device, or switch) in the microgrid. The intelligent agents can execute in accordance with predefined protocols to collectively perform computations that facilitate uninterrupted control of the .
Blueprint for a microwave trapped ion quantum computer.
Lekitsch, Bjoern; Weidt, Sebastian; Fowler, Austin G; Mølmer, Klaus; Devitt, Simon J; Wunderlich, Christof; Hensinger, Winfried K
2017-02-01
The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device. An arbitrarily large quantum computer may best be constructed using a modular approach. We present a blueprint for a trapped ion-based scalable quantum computer module, making it possible to create a scalable quantum computer architecture based on long-wavelength radiation quantum gates. The modules control all operations as stand-alone units, are constructed using silicon microfabrication techniques, and are within reach of current technology. To perform the required quantum computations, the modules make use of long-wavelength radiation-based quantum gate technology. To scale this microwave quantum computer architecture to a large size, we present a fully scalable design that makes use of ion transport between different modules, thereby allowing arbitrarily many modules to be connected to construct a large-scale device. A high error-threshold surface error correction code can be implemented in the proposed architecture to execute fault-tolerant operations. With appropriate adjustments, the proposed modules are also suitable for alternative trapped ion quantum computer architectures, such as schemes using photonic interconnects.
NASA Technical Reports Server (NTRS)
Carroll, Chester C.; Youngblood, John N.; Saha, Aindam
1987-01-01
Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carroll, C.C.; Youngblood, J.N.; Saha, A.
1987-12-01
Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processingmore » elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.« less
SU (2) lattice gauge theory simulations on Fermi GPUs
NASA Astrophysics Data System (ADS)
Cardoso, Nuno; Bicudo, Pedro
2011-05-01
In this work we explore the performance of CUDA in quenched lattice SU (2) simulations. CUDA, NVIDIA Compute Unified Device Architecture, is a hardware and software architecture developed by NVIDIA for computing on the GPU. We present an analysis and performance comparison between the GPU and CPU in single and double precision. Analyses with multiple GPUs and two different architectures (G200 and Fermi architectures) are also presented. In order to obtain a high performance, the code must be optimized for the GPU architecture, i.e., an implementation that exploits the memory hierarchy of the CUDA programming model. We produce codes for the Monte Carlo generation of SU (2) lattice gauge configurations, for the mean plaquette, for the Polyakov Loop at finite T and for the Wilson loop. We also present results for the potential using many configurations (50,000) without smearing and almost 2000 configurations with APE smearing. With two Fermi GPUs we have achieved an excellent performance of 200× the speed over one CPU, in single precision, around 110 Gflops/s. We also find that, using the Fermi architecture, double precision computations for the static quark-antiquark potential are not much slower (less than 2× slower) than single precision computations.
Multiprocessor architecture: Synthesis and evaluation
NASA Technical Reports Server (NTRS)
Standley, Hilda M.
1990-01-01
Multiprocessor computed architecture evaluation for structural computations is the focus of the research effort described. Results obtained are expected to lead to more efficient use of existing architectures and to suggest designs for new, application specific, architectures. The brief descriptions given outline a number of related efforts directed toward this purpose. The difficulty is analyzing an existing architecture or in designing a new computer architecture lies in the fact that the performance of a particular architecture, within the context of a given application, is determined by a number of factors. These include, but are not limited to, the efficiency of the computation algorithm, the programming language and support environment, the quality of the program written in the programming language, the multiplicity of the processing elements, the characteristics of the individual processing elements, the interconnection network connecting processors and non-local memories, and the shared memory organization covering the spectrum from no shared memory (all local memory) to one global access memory. These performance determiners may be loosely classified as being software or hardware related. This distinction is not clear or even appropriate in many cases. The effect of the choice of algorithm is ignored by assuming that the algorithm is specified as given. Effort directed toward the removal of the effect of the programming language and program resulted in the design of a high-level parallel programming language. Two characteristics of the fundamental structure of the architecture (memory organization and interconnection network) are examined.
NASA Technical Reports Server (NTRS)
Boriakoff, Valentin
1994-01-01
The goal of this project was the feasibility study of a particular architecture of a digital signal processing machine operating in real time which could do in a pipeline fashion the computation of the fast Fourier transform (FFT) of a time-domain sampled complex digital data stream. The particular architecture makes use of simple identical processors (called inner product processors) in a linear organization called a systolic array. Through computer simulation the new architecture to compute the FFT with systolic arrays was proved to be viable, and computed the FFT correctly and with the predicted particulars of operation. Integrated circuits to compute the operations expected of the vital node of the systolic architecture were proven feasible, and even with a 2 micron VLSI technology can execute the required operations in the required time. Actual construction of the integrated circuits was successful in one variant (fixed point) and unsuccessful in the other (floating point).
An S N Algorithm for Modern Architectures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Baker, Randal Scott
2016-08-29
LANL discrete ordinates transport packages are required to perform large, computationally intensive time-dependent calculations on massively parallel architectures, where even a single such calculation may need many months to complete. While KBA methods scale out well to very large numbers of compute nodes, we are limited by practical constraints on the number of such nodes we can actually apply to any given calculation. Instead, we describe a modified KBA algorithm that allows realization of the reductions in solution time offered by both the current, and future, architectural changes within a compute node.
Hierarchial parallel computer architecture defined by computational multidisciplinary mechanics
NASA Technical Reports Server (NTRS)
Padovan, Joe; Gute, Doug; Johnson, Keith
1989-01-01
The goal is to develop an architecture for parallel processors enabling optimal handling of multi-disciplinary computation of fluid-solid simulations employing finite element and difference schemes. The goals, philosphical and modeling directions, static and dynamic poly trees, example problems, interpolative reduction, the impact on solvers are shown in viewgraph form.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Uhr, L.
1987-01-01
This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.
Computer Architecture's Changing Role in Rebooting Computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeBenedictis, Erik P.
In this paper, Windows 95 started the Wintel era, in which Microsoft Windows running on Intel x86 microprocessors dominated the computer industry and changed the world. Retaining the x86 instruction set across many generations let users buy new and more capable microprocessors without having to buy software to work with new architectures.
Computer Architecture's Changing Role in Rebooting Computing
DeBenedictis, Erik P.
2017-04-26
In this paper, Windows 95 started the Wintel era, in which Microsoft Windows running on Intel x86 microprocessors dominated the computer industry and changed the world. Retaining the x86 instruction set across many generations let users buy new and more capable microprocessors without having to buy software to work with new architectures.
Design of a fault tolerant airborne digital computer. Volume 1: Architecture
NASA Technical Reports Server (NTRS)
Wensley, J. H.; Levitt, K. N.; Green, M. W.; Goldberg, J.; Neumann, P. G.
1973-01-01
This volume is concerned with the architecture of a fault tolerant digital computer for an advanced commercial aircraft. All of the computations of the aircraft, including those presently carried out by analogue techniques, are to be carried out in this digital computer. Among the important qualities of the computer are the following: (1) The capacity is to be matched to the aircraft environment. (2) The reliability is to be selectively matched to the criticality and deadline requirements of each of the computations. (3) The system is to be readily expandable. contractible, and (4) The design is to appropriate to post 1975 technology. Three candidate architectures are discussed and assessed in terms of the above qualities. Of the three candidates, a newly conceived architecture, Software Implemented Fault Tolerance (SIFT), provides the best match to the above qualities. In addition SIFT is particularly simple and believable. The other candidates, Bus Checker System (BUCS), also newly conceived in this project, and the Hopkins multiprocessor are potentially more efficient than SIFT in the use of redundancy, but otherwise are not as attractive.
Using a software-defined computer in teaching the basics of computer architecture and operation
NASA Astrophysics Data System (ADS)
Kosowska, Julia; Mazur, Grzegorz
2017-08-01
The paper describes the concept and implementation of SDC_One software-defined computer designed for experimental and didactic purposes. Equipped with extensive hardware monitoring mechanisms, the device enables the students to monitor the computer's operation on bus transfer cycle or instruction cycle basis, providing the practical illustration of basic aspects of computer's operation. In the paper, we describe the hardware monitoring capabilities of SDC_One and some scenarios of using it in teaching the basics of computer architecture and microprocessor operation.
A Serial Bus Architecture for Parallel Processing Systems
1986-09-01
pins are needed to effect the data transfer. As Integrated Circuits grow in computational power, more communication capacity is needed, pushing...chip. The wider the communication path the more pins are needed to effect the data transfer. As Integrated Circuits grow in computational power, more...13 2. A Suitable Architecture Sought 14 II. OPTIMUM ARCHITECTURE OF LARGE INTEGRATED A. PARTIONING SILICON FOR MAXIMUM 1? 1. Transistor
Partitioning in Avionics Architectures: Requirements, Mechanisms, and Assurance
NASA Technical Reports Server (NTRS)
Rushby, John
1999-01-01
Automated aircraft control has traditionally been divided into distinct "functions" that are implemented separately (e.g., autopilot, autothrottle, flight management); each function has its own fault-tolerant computer system, and dependencies among different functions are generally limited to the exchange of sensor and control data. A by-product of this "federated" architecture is that faults are strongly contained within the computer system of the function where they occur and cannot readily propagate to affect the operation of other functions. More modern avionics architectures contemplate supporting multiple functions on a single, shared, fault-tolerant computer system where natural fault containment boundaries are less sharply defined. Partitioning uses appropriate hardware and software mechanisms to restore strong fault containment to such integrated architectures. This report examines the requirements for partitioning, mechanisms for their realization, and issues in providing assurance for partitioning. Because partitioning shares some concerns with computer security, security models are reviewed and compared with the concerns of partitioning.
Modeling driver behavior in a cognitive architecture.
Salvucci, Dario D
2006-01-01
This paper explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system. Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to simulate driver behavior and explore the parameters and constraints of this behavior. An integrated driver model developed in the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture is described that focuses on the component processes of control, monitoring, and decision making in a multilane highway environment. This model accounts for the steering profiles, lateral position profiles, and gaze distributions of human drivers during lane keeping, curve negotiation, and lane changing. The model demonstrates how cognitive architectures facilitate understanding of driver behavior in the context of general human abilities and constraints and how the driving domain benefits cognitive architectures by pushing model development toward more complex, realistic tasks. The model can also serve as a core computational engine for practical applications that predict and recognize driver behavior and distraction.
Advanced cloud fault tolerance system
NASA Astrophysics Data System (ADS)
Sumangali, K.; Benny, Niketa
2017-11-01
Cloud computing has become a prevalent on-demand service on the internet to store, manage and process data. A pitfall that accompanies cloud computing is the failures that can be encountered in the cloud. To overcome these failures, we require a fault tolerance mechanism to abstract faults from users. We have proposed a fault tolerant architecture, which is a combination of proactive and reactive fault tolerance. This architecture essentially increases the reliability and the availability of the cloud. In the future, we would like to compare evaluations of our proposed architecture with existing architectures and further improve it.
Heavy Lift Vehicle (HLV) Avionics Flight Computing Architecture Study
NASA Technical Reports Server (NTRS)
Hodson, Robert F.; Chen, Yuan; Morgan, Dwayne R.; Butler, A. Marc; Sdhuh, Joseph M.; Petelle, Jennifer K.; Gwaltney, David A.; Coe, Lisa D.; Koelbl, Terry G.; Nguyen, Hai D.
2011-01-01
A NASA multi-Center study team was assembled from LaRC, MSFC, KSC, JSC and WFF to examine potential flight computing architectures for a Heavy Lift Vehicle (HLV) to better understand avionics drivers. The study examined Design Reference Missions (DRMs) and vehicle requirements that could impact the vehicles avionics. The study considered multiple self-checking and voting architectural variants and examined reliability, fault-tolerance, mass, power, and redundancy management impacts. Furthermore, a goal of the study was to develop the skills and tools needed to rapidly assess additional architectures should requirements or assumptions change.
The new landscape of parallel computer architecture
NASA Astrophysics Data System (ADS)
Shalf, John
2007-07-01
The past few years has seen a sea change in computer architecture that will impact every facet of our society as every electronic device from cell phone to supercomputer will need to confront parallelism of unprecedented scale. Whereas the conventional multicore approach (2, 4, and even 8 cores) adopted by the computing industry will eventually hit a performance plateau, the highest performance per watt and per chip area is achieved using manycore technology (hundreds or even thousands of cores). However, fully unleashing the potential of the manycore approach to ensure future advances in sustained computational performance will require fundamental advances in computer architecture and programming models that are nothing short of reinventing computing. In this paper we examine the reasons behind the movement to exponentially increasing parallelism, and its ramifications for system design, applications and programming models.
Architecutres, Models, Algorithms, and Software Tools for Configurable Computing
2000-03-06
and J.G. Nash. The gated interconnection network for dynamic programming. Plenum, 1988 . [18] Ju wook Jang, Heonchul Park, and Viktor K. Prasanna. A ...Sep. 1997. [2] C. Ebeling, D. C. Cronquist , P. Franklin and C. Fisher, "RaPiD - A configurable computing architecture for compute-intensive...ABSTRACT (Maximum 200 words) The Models, Algorithms, and Architectures for Reconfigurable Computing (MAARC) project developed a sound framework for
Blueprint for a microwave trapped ion quantum computer
Lekitsch, Bjoern; Weidt, Sebastian; Fowler, Austin G.; Mølmer, Klaus; Devitt, Simon J.; Wunderlich, Christof; Hensinger, Winfried K.
2017-01-01
The availability of a universal quantum computer may have a fundamental impact on a vast number of research fields and on society as a whole. An increasingly large scientific and industrial community is working toward the realization of such a device. An arbitrarily large quantum computer may best be constructed using a modular approach. We present a blueprint for a trapped ion–based scalable quantum computer module, making it possible to create a scalable quantum computer architecture based on long-wavelength radiation quantum gates. The modules control all operations as stand-alone units, are constructed using silicon microfabrication techniques, and are within reach of current technology. To perform the required quantum computations, the modules make use of long-wavelength radiation–based quantum gate technology. To scale this microwave quantum computer architecture to a large size, we present a fully scalable design that makes use of ion transport between different modules, thereby allowing arbitrarily many modules to be connected to construct a large-scale device. A high error–threshold surface error correction code can be implemented in the proposed architecture to execute fault-tolerant operations. With appropriate adjustments, the proposed modules are also suitable for alternative trapped ion quantum computer architectures, such as schemes using photonic interconnects. PMID:28164154
Analysis of Introducing Active Learning Methodologies in a Basic Computer Architecture Course
ERIC Educational Resources Information Center
Arbelaitz, Olatz; José I. Martín; Muguerza, Javier
2015-01-01
This paper presents an analysis of introducing active methodologies in the Computer Architecture course taught in the second year of the Computer Engineering Bachelor's degree program at the University of the Basque Country (UPV/EHU), Spain. The paper reports the experience from three academic years, 2011-2012, 2012-2013, and 2013-2014, in which…
ERIC Educational Resources Information Center
Nikolic, B.; Radivojevic, Z.; Djordjevic, J.; Milutinovic, V.
2009-01-01
Courses in Computer Architecture and Organization are regularly included in Computer Engineering curricula. These courses are usually organized in such a way that students obtain not only a purely theoretical experience, but also a practical understanding of the topics lectured. This practical work is usually done in a laboratory using simulators…
A Project-Based Learning Approach to Programmable Logic Design and Computer Architecture
ERIC Educational Resources Information Center
Kellett, C. M.
2012-01-01
This paper describes a course in programmable logic design and computer architecture as it is taught at the University of Newcastle, Australia. The course is designed around a major design project and has two supplemental assessment tasks that are also described. The context of the Computer Engineering degree program within which the course is…
ERIC Educational Resources Information Center
Stanley, Timothy D.; Wong, Lap Kei; Prigmore, Daniel; Benson, Justin; Fishler, Nathan; Fife, Leslie; Colton, Don
2007-01-01
Students learn better when they both hear and do. In computer architecture courses "doing" can be difficult in small schools without hardware laboratories hosted by computer engineering, electrical engineering, or similar departments. Software solutions exist. Our success with George Mills' Multimedia Logic (MML) is the focus of this paper. MML…
The Role of Sketch in Architecture Design
NASA Astrophysics Data System (ADS)
Li, Yanjin; Ning, Wen
2017-06-01
With the continuous development of computer technology, we rely more and more on the computer and pay more and more attention to the final design results, so that we ignore the importance of the sketch. However, the sketch is the most basic and effective way of architecture design. Based on the study of the sketch of Tjibao Cultural Center of sketch, the paper explores the role of sketch in architecture design .
SU (2) lattice gauge theory simulations on Fermi GPUs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cardoso, Nuno, E-mail: nunocardoso@cftp.ist.utl.p; Bicudo, Pedro, E-mail: bicudo@ist.utl.p
2011-05-10
In this work we explore the performance of CUDA in quenched lattice SU (2) simulations. CUDA, NVIDIA Compute Unified Device Architecture, is a hardware and software architecture developed by NVIDIA for computing on the GPU. We present an analysis and performance comparison between the GPU and CPU in single and double precision. Analyses with multiple GPUs and two different architectures (G200 and Fermi architectures) are also presented. In order to obtain a high performance, the code must be optimized for the GPU architecture, i.e., an implementation that exploits the memory hierarchy of the CUDA programming model. We produce codes formore » the Monte Carlo generation of SU (2) lattice gauge configurations, for the mean plaquette, for the Polyakov Loop at finite T and for the Wilson loop. We also present results for the potential using many configurations (50,000) without smearing and almost 2000 configurations with APE smearing. With two Fermi GPUs we have achieved an excellent performance of 200x the speed over one CPU, in single precision, around 110 Gflops/s. We also find that, using the Fermi architecture, double precision computations for the static quark-antiquark potential are not much slower (less than 2x slower) than single precision computations.« less
Exploration of operator method digital optical computers for application to NASA
NASA Technical Reports Server (NTRS)
1990-01-01
Digital optical computer design has been focused primarily towards parallel (single point-to-point interconnection) implementation. This architecture is compared to currently developing VHSIC systems. Using demonstrated multichannel acousto-optic devices, a figure of merit can be formulated. The focus is on a figure of merit termed Gate Interconnect Bandwidth Product (GIBP). Conventional parallel optical digital computer architecture demonstrates only marginal competitiveness at best when compared to projected semiconductor implements. Global, analog global, quasi-digital, and full digital interconnects are briefly examined as alternative to parallel digital computer architecture. Digital optical computing is becoming a very tough competitor to semiconductor technology since it can support a very high degree of three dimensional interconnect density and high degrees of Fan-In without capacitive loading effects at very low power consumption levels.
Layered Architectures for Quantum Computers and Quantum Repeaters
NASA Astrophysics Data System (ADS)
Jones, Nathan C.
This chapter examines how to organize quantum computers and repeaters using a systematic framework known as layered architecture, where machine control is organized in layers associated with specialized tasks. The framework is flexible and could be used for analysis and comparison of quantum information systems. To demonstrate the design principles in practice, we develop architectures for quantum computers and quantum repeaters based on optically controlled quantum dots, showing how a myriad of technologies must operate synchronously to achieve fault-tolerance. Optical control makes information processing in this system very fast, scalable to large problem sizes, and extendable to quantum communication.
Neural simulations on multi-core architectures.
Eichner, Hubert; Klug, Tobias; Borst, Alexander
2009-01-01
Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i.e. user-transparent load balancing.
Neural Simulations on Multi-Core Architectures
Eichner, Hubert; Klug, Tobias; Borst, Alexander
2009-01-01
Neuroscience is witnessing increasing knowledge about the anatomy and electrophysiological properties of neurons and their connectivity, leading to an ever increasing computational complexity of neural simulations. At the same time, a rather radical change in personal computer technology emerges with the establishment of multi-cores: high-density, explicitly parallel processor architectures for both high performance as well as standard desktop computers. This work introduces strategies for the parallelization of biophysically realistic neural simulations based on the compartmental modeling technique and results of such an implementation, with a strong focus on multi-core architectures and automation, i.e. user-transparent load balancing. PMID:19636393
Advanced flight computer. Special study
NASA Technical Reports Server (NTRS)
Coo, Dennis
1995-01-01
This report documents a special study to define a 32-bit radiation hardened, SEU tolerant flight computer architecture, and to investigate current or near-term technologies and development efforts that contribute to the Advanced Flight Computer (AFC) design and development. An AFC processing node architecture is defined. Each node may consist of a multi-chip processor as needed. The modular, building block approach uses VLSI technology and packaging methods that demonstrate a feasible AFC module in 1998 that meets that AFC goals. The defined architecture and approach demonstrate a clear low-risk, low-cost path to the 1998 production goal, with intermediate prototypes in 1996.
Advanced information processing system for advanced launch system: Avionics architecture synthesis
NASA Technical Reports Server (NTRS)
Lala, Jaynarayan H.; Harper, Richard E.; Jaskowiak, Kenneth R.; Rosch, Gene; Alger, Linda S.; Schor, Andrei L.
1991-01-01
The Advanced Information Processing System (AIPS) is a fault-tolerant distributed computer system architecture that was developed to meet the real time computational needs of advanced aerospace vehicles. One such vehicle is the Advanced Launch System (ALS) being developed jointly by NASA and the Department of Defense to launch heavy payloads into low earth orbit at one tenth the cost (per pound of payload) of the current launch vehicles. An avionics architecture that utilizes the AIPS hardware and software building blocks was synthesized for ALS. The AIPS for ALS architecture synthesis process starting with the ALS mission requirements and ending with an analysis of the candidate ALS avionics architecture is described.
GASP-PL/I Simulation of Integrated Avionic System Processor Architectures. M.S. Thesis
NASA Technical Reports Server (NTRS)
Brent, G. A.
1978-01-01
A development study sponsored by NASA was completed in July 1977 which proposed a complete integration of all aircraft instrumentation into a single modular system. Instead of using the current single-function aircraft instruments, computers compiled and displayed inflight information for the pilot. A processor architecture called the Team Architecture was proposed. This is a hardware/software approach to high-reliability computer systems. A follow-up study of the proposed Team Architecture is reported. GASP-PL/1 simulation models are used to evaluate the operating characteristics of the Team Architecture. The problem, model development, simulation programs and results at length are presented. Also included are program input formats, outputs and listings.
Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment
NASA Technical Reports Server (NTRS)
Duong, Tuan A.; Duong, Vu A.
2012-01-01
A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.
Electromagnetic Physics Models for Parallel Computing Architectures
NASA Astrophysics Data System (ADS)
Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.
2016-10-01
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Results of preliminary performance evaluation and physics validation are presented as well.
Computational structures for robotic computations
NASA Technical Reports Server (NTRS)
Lee, C. S. G.; Chang, P. R.
1987-01-01
The computational problem of inverse kinematics and inverse dynamics of robot manipulators by taking advantage of parallelism and pipelining architectures is discussed. For the computation of inverse kinematic position solution, a maximum pipelined CORDIC architecture has been designed based on a functional decomposition of the closed-form joint equations. For the inverse dynamics computation, an efficient p-fold parallel algorithm to overcome the recurrence problem of the Newton-Euler equations of motion to achieve the time lower bound of O(log sub 2 n) has also been developed.
Yokohama, Noriya
2013-07-01
This report was aimed at structuring the design of architectures and studying performance measurement of a parallel computing environment using a Monte Carlo simulation for particle therapy using a high performance computing (HPC) instance within a public cloud-computing infrastructure. Performance measurements showed an approximately 28 times faster speed than seen with single-thread architecture, combined with improved stability. A study of methods of optimizing the system operations also indicated lower cost.
An Object Oriented Extensible Architecture for Affordable Aerospace Propulsion Systems
NASA Technical Reports Server (NTRS)
Follen, Gregory J.
2003-01-01
Driven by a need to explore and develop propulsion systems that exceeded current computing capabilities, NASA Glenn embarked on a novel strategy leading to the development of an architecture that enables propulsion simulations never thought possible before. Full engine 3 Dimensional Computational Fluid Dynamic propulsion system simulations were deemed impossible due to the impracticality of the hardware and software computing systems required. However, with a software paradigm shift and an embracing of parallel and distributed processing, an architecture was designed to meet the needs of future propulsion system modeling. The author suggests that the architecture designed at the NASA Glenn Research Center for propulsion system modeling has potential for impacting the direction of development of affordable weapons systems currently under consideration by the Applied Vehicle Technology Panel (AVT).
Solving the Cauchy-Riemann equations on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1987-01-01
Discussed is the implementation of a single algorithm on three parallel-vector computers. The algorithm is a relaxation scheme for the solution of the Cauchy-Riemann equations; a set of coupled first order partial differential equations. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, and SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The machine architectures are briefly described. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Conclusions are presented.
Application of Tessellation in Architectural Geometry Design
NASA Astrophysics Data System (ADS)
Chang, Wei
2018-06-01
Tessellation plays a significant role in architectural geometry design, which is widely used both through history of architecture and in modern architectural design with the help of computer technology. Tessellation has been found since the birth of civilization. In terms of dimensions, there are two- dimensional tessellations and three-dimensional tessellations; in terms of symmetry, there are periodic tessellations and aperiodic tessellations. Besides, some special types of tessellations such as Voronoi Tessellation and Delaunay Triangles are also included. Both Geometry and Crystallography, the latter of which is the basic theory of three-dimensional tessellations, need to be studied. In history, tessellation was applied into skins or decorations in architecture. The development of Computer technology enables tessellation to be more powerful, as seen in surface control, surface display and structure design, etc. Therefore, research on the application of tessellation in architectural geometry design is of great necessity in architecture studies.
A single VLSI chip for computing syndromes in the (225, 223) Reed-Solomon decoder
NASA Technical Reports Server (NTRS)
Hsu, I. S.; Truong, T. K.; Shao, H. M.; Deutsch, L. J.
1986-01-01
A description of a single VLSI chip for computing syndromes in the (255, 223) Reed-Solomon decoder is presented. The architecture that leads to this single VLSI chip design makes use of the dual basis multiplication algorithm. The same architecture can be applied to design VLSI chips to compute various kinds of number theoretic transforms.
A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL)
NASA Technical Reports Server (NTRS)
Carroll, Chester C.; Owen, Jeffrey E.
1988-01-01
A direct-execution parallel architecture for the Advanced Continuous Simulation Language (ACSL) is presented which overcomes the traditional disadvantages of simulations executed on a digital computer. The incorporation of parallel processing allows the mapping of simulations into a digital computer to be done in the same inherently parallel manner as they are currently mapped onto an analog computer. The direct-execution format maximizes the efficiency of the executed code since the need for a high level language compiler is eliminated. Resolution is greatly increased over that which is available with an analog computer without the sacrifice in execution speed normally expected with digitial computer simulations. Although this report covers all aspects of the new architecture, key emphasis is placed on the processing element configuration and the microprogramming of the ACLS constructs. The execution times for all ACLS constructs are computed using a model of a processing element based on the AMD 29000 CPU and the AMD 29027 FPU. The increase in execution speed provided by parallel processing is exemplified by comparing the derived execution times of two ACSL programs with the execution times for the same programs executed on a similar sequential architecture.
Evidence of common and separate eye and hand accumulators underlying flexible eye-hand coordination
Jana, Sumitash; Gopal, Atul
2016-01-01
Eye and hand movements are initiated by anatomically separate regions in the brain, and yet these movements can be flexibly coupled and decoupled, depending on the need. The computational architecture that enables this flexible coupling of independent effectors is not understood. Here, we studied the computational architecture that enables flexible eye-hand coordination using a drift diffusion framework, which predicts that the variability of the reaction time (RT) distribution scales with its mean. We show that a common stochastic accumulator to threshold, followed by a noisy effector-dependent delay, explains eye-hand RT distributions and their correlation in a visual search task that required decision-making, while an interactive eye and hand accumulator model did not. In contrast, in an eye-hand dual task, an interactive model better predicted the observed correlations and RT distributions than a common accumulator model. Notably, these two models could only be distinguished on the basis of the variability and not the means of the predicted RT distributions. Additionally, signatures of separate initiation signals were also observed in a small fraction of trials in the visual search task, implying that these distinct computational architectures were not a manifestation of the task design per se. Taken together, our results suggest two unique computational architectures for eye-hand coordination, with task context biasing the brain toward instantiating one of the two architectures. NEW & NOTEWORTHY Previous studies on eye-hand coordination have considered mainly the means of eye and hand reaction time (RT) distributions. Here, we leverage the approximately linear relationship between the mean and standard deviation of RT distributions, as predicted by the drift-diffusion model, to propose the existence of two distinct computational architectures underlying coordinated eye-hand movements. These architectures, for the first time, provide a computational basis for the flexible coupling between eye and hand movements. PMID:27784809
A System Architecture for Efficient Transmission of Massive DNA Sequencing Data.
Sağiroğlu, Mahmut Şamİl; Külekcİ, M Oğuzhan
2017-11-01
The DNA sequencing data analysis pipelines require significant computational resources. In that sense, cloud computing infrastructures appear as a natural choice for this processing. However, the first practical difficulty in reaching the cloud computing services is the transmission of the massive DNA sequencing data from where they are produced to where they will be processed. The daily practice here begins with compressing the data in FASTQ file format, and then sending these data via fast data transmission protocols. In this study, we address the weaknesses in that daily practice and present a new system architecture that incorporates the computational resources available on the client side while dynamically adapting itself to the available bandwidth. Our proposal considers the real-life scenarios, where the bandwidth of the connection between the parties may fluctuate, and also the computing power on the client side may be of any size ranging from moderate personal computers to powerful workstations. The proposed architecture aims at utilizing both the communication bandwidth and the computing resources for satisfying the ultimate goal of reaching the results as early as possible. We present a prototype implementation of the proposed architecture, and analyze several real-life cases, which provide useful insights for the sequencing centers, especially on deciding when to use a cloud service and in what conditions.
Computer graphics in architecture and engineering
NASA Technical Reports Server (NTRS)
Greenberg, D. P.
1975-01-01
The present status of the application of computer graphics to the building profession or architecture and its relationship to other scientific and technical areas were discussed. It was explained that, due to the fragmented nature of architecture and building activities (in contrast to the aerospace industry), a comprehensive, economic utilization of computer graphics in this area is not practical and its true potential cannot now be realized due to the present inability of architects and structural, mechanical, and site engineers to rely on a common data base. Future emphasis will therefore have to be placed on a vertical integration of the construction process and effective use of a three-dimensional data base, rather than on waiting for any technological breakthrough in interactive computing.
Innovative architectures for dense multi-microprocessor computers
NASA Technical Reports Server (NTRS)
Larson, Robert E.
1989-01-01
The purpose is to summarize a Phase 1 SBIR project performed for the NASA/Langley Computational Structural Mechanics Group. The project was performed from February to August 1987. The main objectives of the project were to: (1) expand upon previous research into the application of chordal ring architectures to the general problem of designing multi-microcomputer architectures, (2) attempt to identify a family of chordal rings such that each chordal ring can be simply expanded to produce the next member of the family, (3) perform a preliminary, high-level design of an expandable multi-microprocessor computer based upon chordal rings, (4) analyze the potential use of chordal ring based multi-microprocessors for sparse matrix problems and other applications arising in computational structural mechanics.
Fault tolerant architectures for integrated aircraft electronics systems
NASA Technical Reports Server (NTRS)
Levitt, K. N.; Melliar-Smith, P. M.; Schwartz, R. L.
1983-01-01
Work into possible architectures for future flight control computer systems is described. Ada for Fault-Tolerant Systems, the NETS Network Error-Tolerant System architecture, and voting in asynchronous systems are covered.
HyperForest: A high performance multi-processor architecture for real-time intelligent systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garcia, P. Jr.; Rebeil, J.P.; Pollard, H.
1997-04-01
Intelligent Systems are characterized by the intensive use of computer power. The computer revolution of the last few years is what has made possible the development of the first generation of Intelligent Systems. Software for second generation Intelligent Systems will be more complex and will require more powerful computing engines in order to meet real-time constraints imposed by new robots, sensors, and applications. A multiprocessor architecture was developed that merges the advantages of message-passing and shared-memory structures: expendability and real-time compliance. The HyperForest architecture will provide an expandable real-time computing platform for computationally intensive Intelligent Systems and open the doorsmore » for the application of these systems to more complex tasks in environmental restoration and cleanup projects, flexible manufacturing systems, and DOE`s own production and disassembly activities.« less
Motion camera based on a custom vision sensor and an FPGA architecture
NASA Astrophysics Data System (ADS)
Arias-Estrada, Miguel
1998-09-01
A digital camera for custom focal plane arrays was developed. The camera allows the test and development of analog or mixed-mode arrays for focal plane processing. The camera is used with a custom sensor for motion detection to implement a motion computation system. The custom focal plane sensor detects moving edges at the pixel level using analog VLSI techniques. The sensor communicates motion events using the event-address protocol associated to a temporal reference. In a second stage, a coprocessing architecture based on a field programmable gate array (FPGA) computes the time-of-travel between adjacent pixels. The FPGA allows rapid prototyping and flexible architecture development. Furthermore, the FPGA interfaces the sensor to a compact PC computer which is used for high level control and data communication to the local network. The camera could be used in applications such as self-guided vehicles, mobile robotics and smart surveillance systems. The programmability of the FPGA allows the exploration of further signal processing like spatial edge detection or image segmentation tasks. The article details the motion algorithm, the sensor architecture, the use of the event- address protocol for velocity vector computation and the FPGA architecture used in the motion camera system.
Topical perspective on massive threading and parallelism.
Farber, Robert M
2011-09-01
Unquestionably computer architectures have undergone a recent and noteworthy paradigm shift that now delivers multi- and many-core systems with tens to many thousands of concurrent hardware processing elements per workstation or supercomputer node. GPGPU (General Purpose Graphics Processor Unit) technology in particular has attracted significant attention as new software development capabilities, namely CUDA (Compute Unified Device Architecture) and OpenCL™, have made it possible for students as well as small and large research organizations to achieve excellent speedup for many applications over more conventional computing architectures. The current scientific literature reflects this shift with numerous examples of GPGPU applications that have achieved one, two, and in some special cases, three-orders of magnitude increased computational performance through the use of massive threading to exploit parallelism. Multi-core architectures are also evolving quickly to exploit both massive-threading and massive-parallelism such as the 1.3 million threads Blue Waters supercomputer. The challenge confronting scientists in planning future experimental and theoretical research efforts--be they individual efforts with one computer or collaborative efforts proposing to use the largest supercomputers in the world is how to capitalize on these new massively threaded computational architectures--especially as not all computational problems will scale to massive parallelism. In particular, the costs associated with restructuring software (and potentially redesigning algorithms) to exploit the parallelism of these multi- and many-threaded machines must be considered along with application scalability and lifespan. This perspective is an overview of the current state of threading and parallelize with some insight into the future. Published by Elsevier Inc.
Environmental models are products of the computer architecture and software tools available at the time of development. Scientifically sound algorithms may persist in their original state even as system architectures and software development approaches evolve and progress. Dating...
Modelling parallel programs and multiprocessor architectures with AXE
NASA Technical Reports Server (NTRS)
Yan, Jerry C.; Fineman, Charles E.
1991-01-01
AXE, An Experimental Environment for Parallel Systems, was designed to model and simulate for parallel systems at the process level. It provides an integrated environment for specifying computation models, multiprocessor architectures, data collection, and performance visualization. AXE is being used at NASA-Ames for developing resource management strategies, parallel problem formulation, multiprocessor architectures, and operating system issues related to the High Performance Computing and Communications Program. AXE's simple, structured user-interface enables the user to model parallel programs and machines precisely and efficiently. Its quick turn-around time keeps the user interested and productive. AXE models multicomputers. The user may easily modify various architectural parameters including the number of sites, connection topologies, and overhead for operating system activities. Parallel computations in AXE are represented as collections of autonomous computing objects known as players. Their use and behavior is described. Performance data of the multiprocessor model can be observed on a color screen. These include CPU and message routing bottlenecks, and the dynamic status of the software.
A high performance parallel computing architecture for robust image features
NASA Astrophysics Data System (ADS)
Zhou, Renyan; Liu, Leibo; Wei, Shaojun
2014-03-01
A design of parallel architecture for image feature detection and description is proposed in this article. The major component of this architecture is a 2D cellular network composed of simple reprogrammable processors, enabling the Hessian Blob Detector and Haar Response Calculation, which are the most computing-intensive stage of the Speeded Up Robust Features (SURF) algorithm. Combining this 2D cellular network and dedicated hardware for SURF descriptors, this architecture achieves real-time image feature detection with minimal software in the host processor. A prototype FPGA implementation of the proposed architecture achieves 1318.9 GOPS general pixel processing @ 100 MHz clock and achieves up to 118 fps in VGA (640 × 480) image feature detection. The proposed architecture is stand-alone and scalable so it is easy to be migrated into VLSI implementation.
The RISC (Reduced Instruction Set Computer) Architecture and Computer Performance Evaluation.
1986-03-01
time where the main emphasis of the evaluation process is put on the software . The model is intended to provide a tool for computer architects to use...program, or 3) Was to be implemented in random logic more effec- tively than the equivalent sequence of software instructions. Both data and address...definition is the IEEE standard 729-1983 stating Computer Architecture as: " The process of defining a collection of hardware and software components and
First 3 years of operation of RIACS (Research Institute for Advanced Computer Science) (1983-1985)
NASA Technical Reports Server (NTRS)
Denning, P. J.
1986-01-01
The focus of the Research Institute for Advanced Computer Science (RIACS) is to explore matches between advanced computing architectures and the processes of scientific research. An architecture evaluation of the MIT static dataflow machine, specification of a graphical language for expressing distributed computations, and specification of an expert system for aiding in grid generation for two-dimensional flow problems was initiated. Research projects for 1984 and 1985 are summarized.
Song, Tianqi; Garg, Sudhanshu; Mokhtar, Reem; Bui, Hieu; Reif, John
2018-01-19
A main goal in DNA computing is to build DNA circuits to compute designated functions using a minimal number of DNA strands. Here, we propose a novel architecture to build compact DNA strand displacement circuits to compute a broad scope of functions in an analog fashion. A circuit by this architecture is composed of three autocatalytic amplifiers, and the amplifiers interact to perform computation. We show DNA circuits to compute functions sqrt(x), ln(x) and exp(x) for x in tunable ranges with simulation results. A key innovation in our architecture, inspired by Napier's use of logarithm transforms to compute square roots on a slide rule, is to make use of autocatalytic amplifiers to do logarithmic and exponential transforms in concentration and time. In particular, we convert from the input that is encoded by the initial concentration of the input DNA strand, to time, and then back again to the output encoded by the concentration of the output DNA strand at equilibrium. This combined use of strand-concentration and time encoding of computational values may have impact on other forms of molecular computation.
Performances of multiprocessor multidisk architectures for continuous media storage
NASA Astrophysics Data System (ADS)
Gennart, Benoit A.; Messerli, Vincent; Hersch, Roger D.
1996-03-01
Multimedia interfaces increase the need for large image databases, capable of storing and reading streams of data with strict synchronicity and isochronicity requirements. In order to fulfill these requirements, we consider a parallel image server architecture which relies on arrays of intelligent disk nodes, each disk node being composed of one processor and one or more disks. This contribution analyzes through bottleneck performance evaluation and simulation the behavior of two multi-processor multi-disk architectures: a point-to-point architecture and a shared-bus architecture similar to current multiprocessor workstation architectures. We compare the two architectures on the basis of two multimedia algorithms: the compute-bound frame resizing by resampling and the data-bound disk-to-client stream transfer. The results suggest that the shared bus is a potential bottleneck despite its very high hardware throughput (400Mbytes/s) and that an architecture with addressable local memories located closely to their respective processors could partially remove this bottleneck. The point- to-point architecture is scalable and able to sustain high throughputs for simultaneous compute- bound and data-bound operations.
Electromagnetic physics models for parallel computing architectures
Amadio, G.; Ananya, A.; Apostolakis, J.; ...
2016-11-21
The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part ofmore » the GeantV project. Finally, the results of preliminary performance evaluation and physics validation are presented as well.« less
Architectural Implications of Cloud Computing
2011-10-24
Public Cloud Infrastructure-as-a- Service (IaaS) Software -as-a- Service ( SaaS ) Cloud Computing Types Platform-as-a- Service (PaaS) Based on Type of...Twitter #SEIVirtualForum © 2011 Carnegie Mellon University Software -as-a- Service ( SaaS ) Model of software deployment in which a third-party...and System Solutions (RTSS) Program. Her current interests and projects are in service -oriented architecture (SOA), cloud computing, and context
Generic Software for Emulating Multiprocessor Architectures.
1985-05-01
RD-A157 662 GENERIC SOFTWARE FOR EMULATING MULTIPROCESSOR 1/2 AlRCHITECTURES(J) MASSACHUSETTS INST OF TECH CAMBRIDGE U LRS LAB FOR COMPUTER SCIENCE R...AREA & WORK UNIT NUMBERS MIT Laboratory for Computer Science 545 Technology Square Cambridge, MA 02139 ____________ I I. CONTROLLING OFFICE NAME AND...aide If neceeasy end Identify by block number) Computer architecture, emulation, simulation, dataf low 20. ABSTRACT (Continue an reverse slde It
Sigint Application for Polymorphous Computing Architecture (PCA): Wideband DF
2006-08-01
Polymorphous Computing Architecture (PCA) program as stated by Robert Graybill is to Develop the computing foundation for agile systems by establishing...ubiquitous MUSIC algorithm rely upon an underlying narrowband signal model [8]. In this case, narrowband means that the signal bandwidth is less than...a wideband DF algorithm is needed to compensate for this model inadequacy. Among the various wideband DF techniques available, the coherent signal
Exploring Gigabyte Datasets in Real Time: Architectures, Interfaces and Time-Critical Design
NASA Technical Reports Server (NTRS)
Bryson, Steve; Gerald-Yamasaki, Michael (Technical Monitor)
1998-01-01
Architectures and Interfaces: The implications of real-time interaction on software architecture design: decoupling of interaction/graphics and computation into asynchronous processes. The performance requirements of graphics and computation for interaction. Time management in such an architecture. Examples of how visualization algorithms must be modified for high performance. Brief survey of interaction techniques and design, including direct manipulation and manipulation via widgets. talk discusses how human factors considerations drove the design and implementation of the virtual wind tunnel. Time-Critical Design: A survey of time-critical techniques for both computation and rendering. Emphasis on the assignment of a time budget to both the overall visualization environment and to each individual visualization technique in the environment. The estimation of the benefit and cost of an individual technique. Examples of the modification of visualization algorithms to allow time-critical control.
Hardware architecture design of image restoration based on time-frequency domain computation
NASA Astrophysics Data System (ADS)
Wen, Bo; Zhang, Jing; Jiao, Zipeng
2013-10-01
The image restoration algorithms based on time-frequency domain computation is high maturity and applied widely in engineering. To solve the high-speed implementation of these algorithms, the TFDC hardware architecture is proposed. Firstly, the main module is designed, by analyzing the common processing and numerical calculation. Then, to improve the commonality, the iteration control module is planed for iterative algorithms. In addition, to reduce the computational cost and memory requirements, the necessary optimizations are suggested for the time-consuming module, which include two-dimensional FFT/IFFT and the plural calculation. Eventually, the TFDC hardware architecture is adopted for hardware design of real-time image restoration system. The result proves that, the TFDC hardware architecture and its optimizations can be applied to image restoration algorithms based on TFDC, with good algorithm commonality, hardware realizability and high efficiency.
Takeda, Shuntaro; Furusawa, Akira
2017-09-22
We propose a scalable scheme for optical quantum computing using measurement-induced continuous-variable quantum gates in a loop-based architecture. Here, time-bin-encoded quantum information in a single spatial mode is deterministically processed in a nested loop by an electrically programmable gate sequence. This architecture can process any input state and an arbitrary number of modes with almost minimum resources, and offers a universal gate set for both qubits and continuous variables. Furthermore, quantum computing can be performed fault tolerantly by a known scheme for encoding a qubit in an infinite-dimensional Hilbert space of a single light mode.
NASA Astrophysics Data System (ADS)
Takeda, Shuntaro; Furusawa, Akira
2017-09-01
We propose a scalable scheme for optical quantum computing using measurement-induced continuous-variable quantum gates in a loop-based architecture. Here, time-bin-encoded quantum information in a single spatial mode is deterministically processed in a nested loop by an electrically programmable gate sequence. This architecture can process any input state and an arbitrary number of modes with almost minimum resources, and offers a universal gate set for both qubits and continuous variables. Furthermore, quantum computing can be performed fault tolerantly by a known scheme for encoding a qubit in an infinite-dimensional Hilbert space of a single light mode.
Heterogeneous computing architecture for fast detection of SNP-SNP interactions.
Sluga, Davor; Curk, Tomaz; Zupan, Blaz; Lotric, Uros
2014-06-25
The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems.
Heterogeneous computing architecture for fast detection of SNP-SNP interactions
2014-01-01
Background The extent of data in a typical genome-wide association study (GWAS) poses considerable computational challenges to software tools for gene-gene interaction discovery. Exhaustive evaluation of all interactions among hundreds of thousands to millions of single nucleotide polymorphisms (SNPs) may require weeks or even months of computation. Massively parallel hardware within a modern Graphic Processing Unit (GPU) and Many Integrated Core (MIC) coprocessors can shorten the run time considerably. While the utility of GPU-based implementations in bioinformatics has been well studied, MIC architecture has been introduced only recently and may provide a number of comparative advantages that have yet to be explored and tested. Results We have developed a heterogeneous, GPU and Intel MIC-accelerated software module for SNP-SNP interaction discovery to replace the previously single-threaded computational core in the interactive web-based data exploration program SNPsyn. We report on differences between these two modern massively parallel architectures and their software environments. Their utility resulted in an order of magnitude shorter execution times when compared to the single-threaded CPU implementation. GPU implementation on a single Nvidia Tesla K20 runs twice as fast as that for the MIC architecture-based Xeon Phi P5110 coprocessor, but also requires considerably more programming effort. Conclusions General purpose GPUs are a mature platform with large amounts of computing power capable of tackling inherently parallel problems, but can prove demanding for the programmer. On the other hand the new MIC architecture, albeit lacking in performance reduces the programming effort and makes it up with a more general architecture suitable for a wider range of problems. PMID:24964802
DOE Office of Scientific and Technical Information (OSTI.GOV)
McCaskey, Alexander J.
Hybrid programming models for beyond-CMOS technologies will prove critical for integrating new computing technologies alongside our existing infrastructure. Unfortunately the software infrastructure required to enable this is lacking or not available. XACC is a programming framework for extreme-scale, post-exascale accelerator architectures that integrates alongside existing conventional applications. It is a pluggable framework for programming languages developed for next-gen computing hardware architectures like quantum and neuromorphic computing. It lets computational scientists efficiently off-load classically intractable work to attached accelerators through user-friendly Kernel definitions. XACC makes post-exascale hybrid programming approachable for domain computational scientists.
Application of computational physics within Northrop
NASA Technical Reports Server (NTRS)
George, M. W.; Ling, R. T.; Mangus, J. F.; Thompkins, W. T.
1987-01-01
An overview of Northrop programs in computational physics is presented. These programs depend on access to today's supercomputers, such as the Numerical Aerodynamical Simulator (NAS), and future growth on the continuing evolution of computational engines. Descriptions here are concentrated on the following areas: computational fluid dynamics (CFD), computational electromagnetics (CEM), computer architectures, and expert systems. Current efforts and future directions in these areas are presented. The impact of advances in the CFD area is described, and parallels are drawn to analagous developments in CEM. The relationship between advances in these areas and the development of advances (parallel) architectures and expert systems is also presented.
All-memristive neuromorphic computing with level-tuned neurons
NASA Astrophysics Data System (ADS)
Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos
2016-09-01
In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.
All-memristive neuromorphic computing with level-tuned neurons.
Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos
2016-09-02
In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.
Specialized computer architectures for computational aerodynamics
NASA Technical Reports Server (NTRS)
Stevenson, D. K.
1978-01-01
In recent years, computational fluid dynamics has made significant progress in modelling aerodynamic phenomena. Currently, one of the major barriers to future development lies in the compute-intensive nature of the numerical formulations and the relative high cost of performing these computations on commercially available general purpose computers, a cost high with respect to dollar expenditure and/or elapsed time. Today's computing technology will support a program designed to create specialized computing facilities to be dedicated to the important problems of computational aerodynamics. One of the still unresolved questions is the organization of the computing components in such a facility. The characteristics of fluid dynamic problems which will have significant impact on the choice of computer architecture for a specialized facility are reviewed.
Efficient architecture for spike sorting in reconfigurable hardware.
Hwang, Wen-Jyi; Lee, Wei-Hao; Lin, Shiow-Jyu; Lai, Sheng-Ying
2013-11-01
This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA). It is embedded in a System-on-Chip (SOC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation.
Hybrid parallel computing architecture for multiview phase shifting
NASA Astrophysics Data System (ADS)
Zhong, Kai; Li, Zhongwei; Zhou, Xiaohui; Shi, Yusheng; Wang, Congjun
2014-11-01
The multiview phase-shifting method shows its powerful capability in achieving high resolution three-dimensional (3-D) shape measurement. Unfortunately, this ability results in very high computation costs and 3-D computations have to be processed offline. To realize real-time 3-D shape measurement, a hybrid parallel computing architecture is proposed for multiview phase shifting. In this architecture, the central processing unit can co-operate with the graphic processing unit (GPU) to achieve hybrid parallel computing. The high computation cost procedures, including lens distortion rectification, phase computation, correspondence, and 3-D reconstruction, are implemented in GPU, and a three-layer kernel function model is designed to simultaneously realize coarse-grained and fine-grained paralleling computing. Experimental results verify that the developed system can perform 50 fps (frame per second) real-time 3-D measurement with 260 K 3-D points per frame. A speedup of up to 180 times is obtained for the performance of the proposed technique using a NVIDIA GT560Ti graphics card rather than a sequential C in a 3.4 GHZ Inter Core i7 3770.
The science of computing - Parallel computation
NASA Technical Reports Server (NTRS)
Denning, P. J.
1985-01-01
Although parallel computation architectures have been known for computers since the 1920s, it was only in the 1970s that microelectronic components technologies advanced to the point where it became feasible to incorporate multiple processors in one machine. Concommitantly, the development of algorithms for parallel processing also lagged due to hardware limitations. The speed of computing with solid-state chips is limited by gate switching delays. The physical limit implies that a 1 Gflop operational speed is the maximum for sequential processors. A computer recently introduced features a 'hypercube' architecture with 128 processors connected in networks at 5, 6 or 7 points per grid, depending on the design choice. Its computing speed rivals that of supercomputers, but at a fraction of the cost. The added speed with less hardware is due to parallel processing, which utilizes algorithms representing different parts of an equation that can be broken into simpler statements and processed simultaneously. Present, highly developed computer languages like FORTRAN, PASCAL, COBOL, etc., rely on sequential instructions. Thus, increased emphasis will now be directed at parallel processing algorithms to exploit the new architectures.
Analog Computation by DNA Strand Displacement Circuits.
Song, Tianqi; Garg, Sudhanshu; Mokhtar, Reem; Bui, Hieu; Reif, John
2016-08-19
DNA circuits have been widely used to develop biological computing devices because of their high programmability and versatility. Here, we propose an architecture for the systematic construction of DNA circuits for analog computation based on DNA strand displacement. The elementary gates in our architecture include addition, subtraction, and multiplication gates. The input and output of these gates are analog, which means that they are directly represented by the concentrations of the input and output DNA strands, respectively, without requiring a threshold for converting to Boolean signals. We provide detailed domain designs and kinetic simulations of the gates to demonstrate their expected performance. On the basis of these gates, we describe how DNA circuits to compute polynomial functions of inputs can be built. Using Taylor Series and Newton Iteration methods, functions beyond the scope of polynomials can also be computed by DNA circuits built upon our architecture.
Advanced Architectures for Astrophysical Supercomputing
NASA Astrophysics Data System (ADS)
Barsdell, B. R.; Barnes, D. G.; Fluke, C. J.
2010-12-01
Astronomers have come to rely on the increasing performance of computers to reduce, analyze, simulate and visualize their data. In this environment, faster computation can mean more science outcomes or the opening up of new parameter spaces for investigation. If we are to avoid major issues when implementing codes on advanced architectures, it is important that we have a solid understanding of our algorithms. A recent addition to the high-performance computing scene that highlights this point is the graphics processing unit (GPU). The hardware originally designed for speeding-up graphics rendering in video games is now achieving speed-ups of O(100×) in general-purpose computation - performance that cannot be ignored. We are using a generalized approach, based on the analysis of astronomy algorithms, to identify the optimal problem-types and techniques for taking advantage of both current GPU hardware and future developments in computing architectures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lala, J.H.; Nagle, G.A.; Harper, R.E.
1993-05-01
The Maglev control computer system should be designed to verifiably possess high reliability and safety as well as high availability to make Maglev a dependable and attractive transportation alternative to the public. A Maglev control computer system has been designed using a design-for-validation methodology developed earlier under NASA and SDIO sponsorship for real-time aerospace applications. The present study starts by defining the maglev mission scenario and ends with the definition of a maglev control computer architecture. Key intermediate steps included definitions of functional and dependability requirements, synthesis of two candidate architectures, development of qualitative and quantitative evaluation criteria, and analyticalmore » modeling of the dependability characteristics of the two architectures. Finally, the applicability of the design-for-validation methodology was also illustrated by applying it to the German Transrapid TR07 maglev control system.« less
Computer Security Primer: Systems Architecture, Special Ontology and Cloud Virtual Machines
ERIC Educational Resources Information Center
Waguespack, Leslie J.
2014-01-01
With the increasing proliferation of multitasking and Internet-connected devices, security has reemerged as a fundamental design concern in information systems. The shift of IS curricula toward a largely organizational perspective of security leaves little room for focus on its foundation in systems architecture, the computational underpinnings of…
Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Choudhary, Alok Nidhi
1989-01-01
Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.
ATCA for Machines-- Advanced Telecommunications Computing Architecture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Larsen, R.S.; /SLAC
2008-04-22
The Advanced Telecommunications Computing Architecture is a new industry open standard for electronics instrument modules and shelves being evaluated for the International Linear Collider (ILC). It is the first industrial standard designed for High Availability (HA). ILC availability simulations have shown clearly that the capabilities of ATCA are needed in order to achieve acceptable integrated luminosity. The ATCA architecture looks attractive for beam instruments and detector applications as well. This paper provides an overview of ongoing R&D including application of HA principles to power electronics systems.
NASA Astrophysics Data System (ADS)
Kelley, Troy D.; McGhee, S.
2013-05-01
This paper describes the ongoing development of a robotic control architecture that inspired by computational cognitive architectures from the discipline of cognitive psychology. The Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS) combines symbolic and sub-symbolic representations of knowledge into a unified control architecture. The new architecture leverages previous work in cognitive architectures, specifically the development of the Adaptive Character of Thought-Rational (ACT-R) and Soar. This paper details current work on learning from episodes or events. The use of episodic memory as a learning mechanism has, until recently, been largely ignored by computational cognitive architectures. This paper details work on metric level episodic memory streams and methods for translating episodes into abstract schemas. The presentation will include research on learning through novelty and self generated feedback mechanisms for autonomous systems.
Sensing and perception: Connectionist approaches to subcognitive computing
NASA Technical Reports Server (NTRS)
Skrrypek, J.
1987-01-01
New approaches to machine sensing and perception are presented. The motivation for crossdisciplinary studies of perception in terms of AI and neurosciences is suggested. The question of computing architecture granularity as related to global/local computation underlying perceptual function is considered and examples of two environments are given. Finally, the examples of using one of the environments, UCLA PUNNS, to study neural architectures for visual function are presented.
Computer architecture evaluation for structural dynamics computations: Project summary
NASA Technical Reports Server (NTRS)
Standley, Hilda M.
1989-01-01
The intent of the proposed effort is the examination of the impact of the elements of parallel architectures on the performance realized in a parallel computation. To this end, three major projects are developed: a language for the expression of high level parallelism, a statistical technique for the synthesis of multicomputer interconnection networks based upon performance prediction, and a queueing model for the analysis of shared memory hierarchies.
2009-03-01
SENSOR NETWORKS THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and...hierarchical, and Secure Lock within a wireless sensor network (WSN) under the Hubenko architecture. Using a Matlab computer simulation, the impact of the...rekeying protocol should be applied given particular network parameters, such as WSN size. 10 1.3 Experimental Approach A computer simulation in
Kazakis, Georgios; Kanellopoulos, Ioannis; Sotiropoulos, Stefanos; Lagaros, Nikos D
2017-10-01
Construction industry has a major impact on the environment that we spend most of our life. Therefore, it is important that the outcome of architectural intuition performs well and complies with the design requirements. Architects usually describe as "optimal design" their choice among a rather limited set of design alternatives, dictated by their experience and intuition. However, modern design of structures requires accounting for a great number of criteria derived from multiple disciplines, often of conflicting nature. Such criteria derived from structural engineering, eco-design, bioclimatic and acoustic performance. The resulting vast number of alternatives enhances the need for computer-aided architecture in order to increase the possibility of arriving at a more preferable solution. Therefore, the incorporation of smart, automatic tools in the design process, able to further guide designer's intuition becomes even more indispensable. The principal aim of this study is to present possibilities to integrate automatic computational techniques related to topology optimization in the phase of intuition of civil structures as part of computer aided architectural design. In this direction, different aspects of a new computer aided architectural era related to the interpretation of the optimized designs, difficulties resulted from the increased computational effort and 3D printing capabilities are covered here in.
NASA Technical Reports Server (NTRS)
Smith, Paul H.
1988-01-01
The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.
Architecture for hospital information integration
NASA Astrophysics Data System (ADS)
Chimiak, William J.; Janariz, Daniel L.; Martinez, Ralph
1999-07-01
The ongoing integration of hospital information systems (HIS) continues. Data storage systems, data networks and computers improve, data bases grow and health-care applications increase. Some computer operating systems continue to evolve and some fade. Health care delivery now depends on this computer-assisted environment. The result is the critical harmonization of the various hospital information systems becomes increasingly difficult. The purpose of this paper is to present an architecture for HIS integration that is computer-language-neutral and computer- hardware-neutral for the informatics applications. The proposed architecture builds upon the work done at the University of Arizona on middleware, the work of the National Electrical Manufacturers Association, and the American College of Radiology. It is a fresh approach to allowing applications engineers to access medical data easily and thus concentrates on the application techniques in which they are expert without struggling with medical information syntaxes. The HIS can be modeled using a hierarchy of information sub-systems thus facilitating its understanding. The architecture includes the resulting information model along with a strict but intuitive application programming interface, managed by CORBA. The CORBA requirement facilitates interoperability. It should also reduce software and hardware development times.
FPGA Implementation of Generalized Hebbian Algorithm for Texture Classification
Lin, Shiow-Jyu; Hwang, Wen-Jyi; Lee, Wei-Hao
2012-01-01
This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness. The architecture is separated into three portions: the weight vector updating unit, the principal computation unit and the memory unit. In the weight vector updating unit, the computation of different synaptic weight vectors shares the same circuit for reducing the area costs. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is physically implemented by Field Programmable Gate Array (FPGA). It is embedded in a System-On-Programmable-Chip (SOPC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs. PMID:22778640
NASA Technical Reports Server (NTRS)
Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.
1995-01-01
Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.
Gigaflop architecture, a hardware perspective
NASA Technical Reports Server (NTRS)
Feierbach, G. F.
1978-01-01
Any super computer built in the early 1980s will use components that are available by fall 1978. The architecture of such a system cannot depart radically from current super computers if the software experience painfully acquired from these computers in the 70's is to apply. Given the above constraints, 10 billion floating point operations per second (BFLOPS) are attainable and a problem memory of 512 million (64 bit) words could be supported by the technology of the time. In contrast to this, industry is likely to respond with commercially available machines with a performance of less than 150 MFLOPS. This is due to self-imposed constraints on the manufacturers to provide upward compatible architectures (same instruction set) and systems which can be sold in significant volumes. Since this computing speed is inadequate to meet the demands of computational fluid dynamics, a special processor is required. Issues which are felt to be significant in the pursuit of maximum compute capability in this special processor are discussed.
Using Multimedia for Teaching Analysis in History of Modern Architecture.
ERIC Educational Resources Information Center
Perryman, Garry
This paper presents a case for the development and support of a computer-based interactive multimedia program for teaching analysis in community college architecture design programs. Analysis in architecture design is an extremely important strategy for the teaching of higher-order thinking skills, which senior schools of architecture look for in…
Progress in a novel architecture for high performance processing
NASA Astrophysics Data System (ADS)
Zhang, Zhiwei; Liu, Meng; Liu, Zijun; Du, Xueliang; Xie, Shaolin; Ma, Hong; Ding, Guangxin; Ren, Weili; Zhou, Fabiao; Sun, Wenqin; Wang, Huijuan; Wang, Donglin
2018-04-01
The high performance processing (HPP) is an innovative architecture which targets on high performance computing with excellent power efficiency and computing performance. It is suitable for data intensive applications like supercomputing, machine learning and wireless communication. An example chip with four application-specific integrated circuit (ASIC) cores which is the first generation of HPP cores has been taped out successfully under Taiwan Semiconductor Manufacturing Company (TSMC) 40 nm low power process. The innovative architecture shows great energy efficiency over the traditional central processing unit (CPU) and general-purpose computing on graphics processing units (GPGPU). Compared with MaPU, HPP has made great improvement in architecture. The chip with 32 HPP cores is being developed under TSMC 16 nm field effect transistor (FFC) technology process and is planed to use commercially. The peak performance of this chip can reach 4.3 teraFLOPS (TFLOPS) and its power efficiency is up to 89.5 gigaFLOPS per watt (GFLOPS/W).
Multiple Embedded Processors for Fault-Tolerant Computing
NASA Technical Reports Server (NTRS)
Bolotin, Gary; Watson, Robert; Katanyoutanant, Sunant; Burke, Gary; Wang, Mandy
2005-01-01
A fault-tolerant computer architecture has been conceived in an effort to reduce vulnerability to single-event upsets (spurious bit flips caused by impingement of energetic ionizing particles or photons). As in some prior fault-tolerant architectures, the redundancy needed for fault tolerance is obtained by use of multiple processors in one computer. Unlike prior architectures, the multiple processors are embedded in a single field-programmable gate array (FPGA). What makes this new approach practical is the recent commercial availability of FPGAs that are capable of having multiple embedded processors. A working prototype (see figure) consists of two embedded IBM PowerPC 405 processor cores and a comparator built on a Xilinx Virtex-II Pro FPGA. This relatively simple instantiation of the architecture implements an error-detection scheme. A planned future version, incorporating four processors and two comparators, would correct some errors in addition to detecting them.
A static data flow simulation study at Ames Research Center
NASA Technical Reports Server (NTRS)
Barszcz, Eric; Howard, Lauri S.
1987-01-01
Demands in computational power, particularly in the area of computational fluid dynamics (CFD), led NASA Ames Research Center to study advanced computer architectures. One architecture being studied is the static data flow architecture based on research done by Jack B. Dennis at MIT. To improve understanding of this architecture, a static data flow simulator, written in Pascal, has been implemented for use on a Cray X-MP/48. A matrix multiply and a two-dimensional fast Fourier transform (FFT), two algorithms used in CFD work at Ames, have been run on the simulator. Execution times can vary by a factor of more than 2 depending on the partitioning method used to assign instructions to processing elements. Service time for matching tokens has proved to be a major bottleneck. Loop control and array address calculation overhead can double the execution time. The best sustained MFLOPS rates were less than 50% of the maximum capability of the machine.
Strategies for concurrent processing of complex algorithms in data driven architectures
NASA Technical Reports Server (NTRS)
Stoughton, John W.; Mielke, Roland R.
1988-01-01
The purpose is to document research to develop strategies for concurrent processing of complex algorithms in data driven architectures. The problem domain consists of decision-free algorithms having large-grained, computationally complex primitive operations. Such are often found in signal processing and control applications. The anticipated multiprocessor environment is a data flow architecture containing between two and twenty computing elements. Each computing element is a processor having local program memory, and which communicates with a common global data memory. A new graph theoretic model called ATAMM which establishes rules for relating a decomposed algorithm to its execution in a data flow architecture is presented. The ATAMM model is used to determine strategies to achieve optimum time performance and to develop a system diagnostic software tool. In addition, preliminary work on a new multiprocessor operating system based on the ATAMM specifications is described.
Muller, George; Perkins, Casey J.; Lancaster, Mary J.; MacDonald, Douglas G.; Clements, Samuel L.; Hutton, William J.; Patrick, Scott W.; Key, Bradley Robert
2015-07-28
Computer-implemented security evaluation methods, security evaluation systems, and articles of manufacture are described. According to one aspect, a computer-implemented security evaluation method includes accessing information regarding a physical architecture and a cyber architecture of a facility, building a model of the facility comprising a plurality of physical areas of the physical architecture, a plurality of cyber areas of the cyber architecture, and a plurality of pathways between the physical areas and the cyber areas, identifying a target within the facility, executing the model a plurality of times to simulate a plurality of attacks against the target by an adversary traversing at least one of the areas in the physical domain and at least one of the areas in the cyber domain, and using results of the executing, providing information regarding a security risk of the facility with respect to the target.
Enterprise application architecture development based on DoDAF and TOGAF
NASA Astrophysics Data System (ADS)
Tao, Zhi-Gang; Luo, Yun-Feng; Chen, Chang-Xin; Wang, Ming-Zhe; Ni, Feng
2017-05-01
For the purpose of supporting the design and analysis of enterprise application architecture, here, we report a tailored enterprise application architecture description framework and its corresponding design method. The presented framework can effectively support service-oriented architecting and cloud computing by creating the metadata model based on architecture content framework (ACF), DoDAF metamodel (DM2) and Cloud Computing Modelling Notation (CCMN). The framework also makes an effort to extend and improve the mapping between The Open Group Architecture Framework (TOGAF) application architectural inputs/outputs, deliverables and Department of Defence Architecture Framework (DoDAF)-described models. The roadmap of 52 DoDAF-described models is constructed by creating the metamodels of these described models and analysing the constraint relationship among metamodels. By combining the tailored framework and the roadmap, this article proposes a service-oriented enterprise application architecture development process. Finally, a case study is presented to illustrate the results of implementing the tailored framework in the Southern Base Management Support and Information Platform construction project using the development process proposed by the paper.
Selecting a Benchmark Suite to Profile High-Performance Computing (HPC) Machines
2014-11-01
architectures. Machines now contain central processing units (CPUs), graphics processing units (GPUs), and many integrated core ( MIC ) architecture all...evaluate the feasibility and applicability of a new architecture just released to the market . Researchers are often unsure how available resources will...architectures. Having a suite of programs running on different architectures, such as GPUs, MICs , and CPUs, adds complexity and technical challenges
NASA Technical Reports Server (NTRS)
Fijany, Amir (Inventor); Bejczy, Antal K. (Inventor)
1993-01-01
This is a real-time robotic controller and simulator which is a MIMD-SIMD parallel architecture for interfacing with an external host computer and providing a high degree of parallelism in computations for robotic control and simulation. It includes a host processor for receiving instructions from the external host computer and for transmitting answers to the external host computer. There are a plurality of SIMD microprocessors, each SIMD processor being a SIMD parallel processor capable of exploiting fine grain parallelism and further being able to operate asynchronously to form a MIMD architecture. Each SIMD processor comprises a SIMD architecture capable of performing two matrix-vector operations in parallel while fully exploiting parallelism in each operation. There is a system bus connecting the host processor to the plurality of SIMD microprocessors and a common clock providing a continuous sequence of clock pulses. There is also a ring structure interconnecting the plurality of SIMD microprocessors and connected to the clock for providing the clock pulses to the SIMD microprocessors and for providing a path for the flow of data and instructions between the SIMD microprocessors. The host processor includes logic for controlling the RRCS by interpreting instructions sent by the external host computer, decomposing the instructions into a series of computations to be performed by the SIMD microprocessors, using the system bus to distribute associated data among the SIMD microprocessors, and initiating activity of the SIMD microprocessors to perform the computations on the data by procedure call.
NASA Astrophysics Data System (ADS)
Mehta, Neville; Kompalli, Suryaprakash; Chaudhary, Vipin
Teleradiology is the electronic transmission of radiological patient images, such as x-rays, CT, or MR across multiple locations. The goal could be interpretation, consultation, or medical records keeping. Information technology solutions have enabled electronic records and their associated benefits are evident in health care today. However, salient aspects of collaborative interfaces, and computer assisted diagnostic (CAD) tools are yet to be integrated into workflow designs. The Computer Assisted Diagnostics and Interventions (CADI) group at the University at Buffalo has developed an architecture that facilitates web-enabled use of CAD tools, along with the novel concept of synchronized collaboration. The architecture can support multiple teleradiology applications and case studies are presented here.
Design of a modular digital computer system, CDRL no. D001, final design plan
NASA Technical Reports Server (NTRS)
Easton, R. A.
1975-01-01
The engineering breadboard implementation for the CDRL no. D001 modular digital computer system developed during design of the logic system was documented. This effort followed the architecture study completed and documented previously, and was intended to verify the concepts of a fault tolerant, automatically reconfigurable, modular version of the computer system conceived during the architecture study. The system has a microprogrammed 32 bit word length, general register architecture and an instruction set consisting of a subset of the IBM System 360 instruction set plus additional fault tolerance firmware. The following areas were covered: breadboard packaging, central control element, central processing element, memory, input/output processor, and maintenance/status panel and electronics.
NASA Astrophysics Data System (ADS)
Dave, Gaurav P.; Sureshkumar, N.; Blessy Trencia Lincy, S. S.
2017-11-01
Current trend in processor manufacturing focuses on multi-core architectures rather than increasing the clock speed for performance improvement. Graphic processors have become as commodity hardware for providing fast co-processing in computer systems. Developments in IoT, social networking web applications, big data created huge demand for data processing activities and such kind of throughput intensive applications inherently contains data level parallelism which is more suited for SIMD architecture based GPU. This paper reviews the architectural aspects of multi/many core processors and graphics processors. Different case studies are taken to compare performance of throughput computing applications using shared memory programming in OpenMP and CUDA API based programming.
Examining the architecture of cellular computing through a comparative study with a computer
Wang, Degeng; Gribskov, Michael
2005-01-01
The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software–hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's ‘hardware’ equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the ‘bandwidth’ of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed. PMID:16849179
Examining the architecture of cellular computing through a comparative study with a computer.
Wang, Degeng; Gribskov, Michael
2005-06-22
The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software-hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's "hardware" equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the "bandwidth" of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed.
SNAVA-A real-time multi-FPGA multi-model spiking neural network simulation architecture.
Sripad, Athul; Sanchez, Giovanny; Zapata, Mireya; Pirrone, Vito; Dorta, Taho; Cambria, Salvatore; Marti, Albert; Krishnamourthy, Karthikeyan; Madrenas, Jordi
2018-01-01
Spiking Neural Networks (SNN) for Versatile Applications (SNAVA) simulation platform is a scalable and programmable parallel architecture that supports real-time, large-scale, multi-model SNN computation. This parallel architecture is implemented in modern Field-Programmable Gate Arrays (FPGAs) devices to provide high performance execution and flexibility to support large-scale SNN models. Flexibility is defined in terms of programmability, which allows easy synapse and neuron implementation. This has been achieved by using a special-purpose Processing Elements (PEs) for computing SNNs, and analyzing and customizing the instruction set according to the processing needs to achieve maximum performance with minimum resources. The parallel architecture is interfaced with customized Graphical User Interfaces (GUIs) to configure the SNN's connectivity, to compile the neuron-synapse model and to monitor SNN's activity. Our contribution intends to provide a tool that allows to prototype SNNs faster than on CPU/GPU architectures but significantly cheaper than fabricating a customized neuromorphic chip. This could be potentially valuable to the computational neuroscience and neuromorphic engineering communities. Copyright © 2017 Elsevier Ltd. All rights reserved.
Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing
Kudithipudi, Dhireesha; Saleh, Qutaiba; Merkel, Cory; Thesing, James; Wysocki, Bryant
2016-01-01
Reservoir computing (RC) is gaining traction in several signal processing domains, owing to its non-linear stateful computation, spatiotemporal encoding, and reduced training complexity over recurrent neural networks (RNNs). Previous studies have shown the effectiveness of software-based RCs for a wide spectrum of applications. A parallel body of work indicates that realizing RNN architectures using custom integrated circuits and reconfigurable hardware platforms yields significant improvements in power and latency. In this research, we propose a neuromemristive RC architecture, with doubly twisted toroidal structure, that is validated for biosignal processing applications. We exploit the device mismatch to implement the random weight distributions within the reservoir and propose mixed-signal subthreshold circuits for energy efficiency. A comprehensive analysis is performed to compare the efficiency of the neuromemristive RC architecture in both digital(reconfigurable) and subthreshold mixed-signal realizations. Both Electroencephalogram (EEG) and Electromyogram (EMG) biosignal benchmarks are used for validating the RC designs. The proposed RC architecture demonstrated an accuracy of 90 and 84% for epileptic seizure detection and EMG prosthetic finger control, respectively. PMID:26869876
Yoo, Dongjin
2012-07-01
Advanced additive manufacture (AM) techniques are now being developed to fabricate scaffolds with controlled internal pore architectures in the field of tissue engineering. In general, these techniques use a hybrid method which combines computer-aided design (CAD) with computer-aided manufacturing (CAM) tools to design and fabricate complicated three-dimensional (3D) scaffold models. The mathematical descriptions of micro-architectures along with the macro-structures of the 3D scaffold models are limited by current CAD technologies as well as by the difficulty of transferring the designed digital models to standard formats for fabrication. To overcome these difficulties, we have developed an efficient internal pore architecture design system based on triply periodic minimal surface (TPMS) unit cell libraries and associated computational methods to assemble TPMS unit cells into an entire scaffold model. In addition, we have developed a process planning technique based on TPMS internal architecture pattern of unit cells to generate tool paths for freeform fabrication of tissue engineering porous scaffolds. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
Embedded Data Processor and Portable Computer Technology testbeds
NASA Technical Reports Server (NTRS)
Alena, Richard; Liu, Yuan-Kwei; Goforth, Andre; Fernquist, Alan R.
1993-01-01
Attention is given to current activities in the Embedded Data Processor and Portable Computer Technology testbed configurations that are part of the Advanced Data Systems Architectures Testbed at the Information Sciences Division at NASA Ames Research Center. The Embedded Data Processor Testbed evaluates advanced microprocessors for potential use in mission and payload applications within the Space Station Freedom Program. The Portable Computer Technology (PCT) Testbed integrates and demonstrates advanced portable computing devices and data system architectures. The PCT Testbed uses both commercial and custom-developed devices to demonstrate the feasibility of functional expansion and networking for portable computers in flight missions.
A supportive architecture for CFD-based design optimisation
NASA Astrophysics Data System (ADS)
Li, Ni; Su, Zeya; Bi, Zhuming; Tian, Chao; Ren, Zhiming; Gong, Guanghong
2014-03-01
Multi-disciplinary design optimisation (MDO) is one of critical methodologies to the implementation of enterprise systems (ES). MDO requiring the analysis of fluid dynamics raises a special challenge due to its extremely intensive computation. The rapid development of computational fluid dynamic (CFD) technique has caused a rise of its applications in various fields. Especially for the exterior designs of vehicles, CFD has become one of the three main design tools comparable to analytical approaches and wind tunnel experiments. CFD-based design optimisation is an effective way to achieve the desired performance under the given constraints. However, due to the complexity of CFD, integrating with CFD analysis in an intelligent optimisation algorithm is not straightforward. It is a challenge to solve a CFD-based design problem, which is usually with high dimensions, and multiple objectives and constraints. It is desirable to have an integrated architecture for CFD-based design optimisation. However, our review on existing works has found that very few researchers have studied on the assistive tools to facilitate CFD-based design optimisation. In the paper, a multi-layer architecture and a general procedure are proposed to integrate different CFD toolsets with intelligent optimisation algorithms, parallel computing technique and other techniques for efficient computation. In the proposed architecture, the integration is performed either at the code level or data level to fully utilise the capabilities of different assistive tools. Two intelligent algorithms are developed and embedded with parallel computing. These algorithms, together with the supportive architecture, lay a solid foundation for various applications of CFD-based design optimisation. To illustrate the effectiveness of the proposed architecture and algorithms, the case studies on aerodynamic shape design of a hypersonic cruising vehicle are provided, and the result has shown that the proposed architecture and developed algorithms have performed successfully and efficiently in dealing with the design optimisation with over 200 design variables.
Prospective Architectures for Onboard vs Cloud-Based Decision Making for Unmanned Aerial Systems
NASA Technical Reports Server (NTRS)
Sankararaman, Shankar; Teubert, Christopher
2017-01-01
This paper investigates propsective architectures for decision-making in unmanned aerial systems. When these unmanned vehicles operate in urban environments, there are several sources of uncertainty that affect their behavior, and decision-making algorithms need to be robust to account for these different sources of uncertainty. It is important to account for several risk-factors that affect the flight of these unmanned systems, and facilitate decision-making by taking into consideration these various risk-factors. In addition, there are several technical challenges related to autonomous flight of unmanned aerial systems; these challenges include sensing, obstacle detection, path planning and navigation, trajectory generation and selection, etc. Many of these activities require significant computational power and in many situations, all of these activities need to be performed in real-time. In order to efficiently integrate these activities, it is important to develop a systematic architecture that can facilitate real-time decision-making. Four prospective architectures are discussed in this paper; on one end of the spectrum, the first architecture considers all activities/computations being performed onboard the vehicle whereas on the other end of the spectrum, the fourth and final architecture considers all activities/computations being performed in the cloud, using a new service known as Prognostics as a Service that is being developed at NASA Ames Research Center. The four different architectures are compared, their advantages and disadvantages are explained and conclusions are presented.
NASA Astrophysics Data System (ADS)
Zaveri, Mazad Shaheriar
The semiconductor/computer industry has been following Moore's law for several decades and has reaped the benefits in speed and density of the resultant scaling. Transistor density has reached almost one billion per chip, and transistor delays are in picoseconds. However, scaling has slowed down, and the semiconductor industry is now facing several challenges. Hybrid CMOS/nano technologies, such as CMOL, are considered as an interim solution to some of the challenges. Another potential architectural solution includes specialized architectures for applications/models in the intelligent computing domain, one aspect of which includes abstract computational models inspired from the neuro/cognitive sciences. Consequently in this dissertation, we focus on the hardware implementations of Bayesian Memory (BM), which is a (Bayesian) Biologically Inspired Computational Model (BICM). This model is a simplified version of George and Hawkins' model of the visual cortex, which includes an inference framework based on Judea Pearl's belief propagation. We then present a "hardware design space exploration" methodology for implementing and analyzing the (digital and mixed-signal) hardware for the BM. This particular methodology involves: analyzing the computational/operational cost and the related micro-architecture, exploring candidate hardware components, proposing various custom hardware architectures using both traditional CMOS and hybrid nanotechnology - CMOL, and investigating the baseline performance/price of these architectures. The results suggest that CMOL is a promising candidate for implementing a BM. Such implementations can utilize the very high density storage/computation benefits of these new nano-scale technologies much more efficiently; for example, the throughput per 858 mm2 (TPM) obtained for CMOL based architectures is 32 to 40 times better than the TPM for a CMOS based multiprocessor/multi-FPGA system, and almost 2000 times better than the TPM for a PC implementation. We later use this methodology to investigate the hardware implementations of cortex-scale spiking neural system, which is an approximate neural equivalent of BICM based cortex-scale system. The results of this investigation also suggest that CMOL is a promising candidate to implement such large-scale neuromorphic systems. In general, the assessment of such hypothetical baseline hardware architectures provides the prospects for building large-scale (mammalian cortex-scale) implementations of neuromorphic/Bayesian/intelligent systems using state-of-the-art and beyond state-of-the-art silicon structures.
NASA Astrophysics Data System (ADS)
Lhamon, Michael Earl
A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase-only implementation with lower detection performance than full complex electronic systems. Our study includes pseudo-random pixel encoding techniques for approximating full complex filtering. Optical filter bank implementation is possible and they have the advantage of time averaging the entire filter bank at real time rates. Time-averaged optical filtering is computational comparable to billions of digital operations-per-second. For this reason, we believe future trends in high speed pattern recognition will involve hybrid architectures of both optical and DSP elements.
Super and parallel computers and their impact on civil engineering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kamat, M.P.
1986-01-01
This book presents the papers given at a conference on the use of supercomputers in civil engineering. Topics considered at the conference included solving nonlinear equations on a hypercube, a custom architectured parallel processing system, distributed data processing, algorithms, computer architecture, parallel processing, vector processing, computerized simulation, and cost benefit analysis.
p88110: A Graphical Simulator for Computer Architecture and Organization Courses
ERIC Educational Resources Information Center
Garcia, M. I.; Rodriguez, S.; Perez, A.; Garcia, A.
2009-01-01
Studying fundamental Computer Architecture and Organization topics requires a significant amount of practical work if students are to acquire a good grasp of the theoretical concepts presented in classroom lectures or textbooks. The use of simulators is commonly adopted in order to reach this objective. However, as most of the available…
Component architecture in drug discovery informatics.
Smith, Peter M
2002-05-01
This paper reviews the characteristics of a new model of computing that has been spurred on by the Internet, known as Netcentric computing. Developments in this model led to distributed component architectures, which, although not new ideas, are now realizable with modern tools such as Enterprise Java. The application of this approach to scientific computing, particularly in pharmaceutical discovery research, is discussed and highlighted by a particular case involving the management of biological assay data.
FPGA-based architecture for motion recovering in real-time
NASA Astrophysics Data System (ADS)
Arias-Estrada, Miguel; Maya-Rueda, Selene E.; Torres-Huitzil, Cesar
2002-03-01
A key problem in the computer vision field is the measurement of object motion in a scene. The main goal is to compute an approximation of the 3D motion from the analysis of an image sequence. Once computed, this information can be used as a basis to reach higher level goals in different applications. Motion estimation algorithms pose a significant computational load for the sequential processors limiting its use in practical applications. In this work we propose a hardware architecture for motion estimation in real time based on FPGA technology. The technique used for motion estimation is Optical Flow due to its accuracy, and the density of velocity estimation, however other techniques are being explored. The architecture is composed of parallel modules working in a pipeline scheme to reach high throughput rates near gigaflops. The modules are organized in a regular structure to provide a high degree of flexibility to cover different applications. Some results will be presented and the real-time performance will be discussed and analyzed. The architecture is prototyped in an FPGA board with a Virtex device interfaced to a digital imager.
Parallel, stochastic measurement of molecular surface area.
Juba, Derek; Varshney, Amitabh
2008-08-01
Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.
NASA Technical Reports Server (NTRS)
Torres-Pomales, Wilfredo
2014-01-01
This report presents an example of the application of multi-criteria decision analysis to the selection of an architecture for a safety-critical distributed computer system. The design problem includes constraints on minimum system availability and integrity, and the decision is based on the optimal balance of power, weight and cost. The analysis process includes the generation of alternative architectures, evaluation of individual decision criteria, and the selection of an alternative based on overall value. In this example presented here, iterative application of the quantitative evaluation process made it possible to deliberately generate an alternative architecture that is superior to all others regardless of the relative importance of cost.
Fault tolerant architectures for integrated aircraft electronics systems, task 2
NASA Technical Reports Server (NTRS)
Levitt, K. N.; Melliar-Smith, P. M.; Schwartz, R. L.
1984-01-01
The architectural basis for an advanced fault tolerant on-board computer to succeed the current generation of fault tolerant computers is examined. The network error tolerant system architecture is studied with particular attention to intercluster configurations and communication protocols, and to refined reliability estimates. The diagnosis of faults, so that appropriate choices for reconfiguration can be made is discussed. The analysis relates particularly to the recognition of transient faults in a system with tasks at many levels of priority. The demand driven data-flow architecture, which appears to have possible application in fault tolerant systems is described and work investigating the feasibility of automatic generation of aircraft flight control programs from abstract specifications is reported.
NASA Astrophysics Data System (ADS)
Liu, Lei; Hong, Xiaobin; Wu, Jian; Lin, Jintong
As Grid computing continues to gain popularity in the industry and research community, it also attracts more attention from the customer level. The large number of users and high frequency of job requests in the consumer market make it challenging. Clearly, all the current Client/Server(C/S)-based architecture will become unfeasible for supporting large-scale Grid applications due to its poor scalability and poor fault-tolerance. In this paper, based on our previous works [1, 2], a novel self-organized architecture to realize a highly scalable and flexible platform for Grids is proposed. Experimental results show that this architecture is suitable and efficient for consumer-oriented Grids.
A cognitive computational model inspired by the immune system response.
Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim
2014-01-01
The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.
A Cognitive Computational Model Inspired by the Immune System Response
Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim
2014-01-01
The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective. PMID:25003131
Generic Divide and Conquer Internet-Based Computing
NASA Technical Reports Server (NTRS)
Follen, Gregory J. (Technical Monitor); Radenski, Atanas
2003-01-01
The growth of Internet-based applications and the proliferation of networking technologies have been transforming traditional commercial application areas as well as computer and computational sciences and engineering. This growth stimulates the exploration of Peer to Peer (P2P) software technologies that can open new research and application opportunities not only for the commercial world, but also for the scientific and high-performance computing applications community. The general goal of this project is to achieve better understanding of the transition to Internet-based high-performance computing and to develop solutions for some of the technical challenges of this transition. In particular, we are interested in creating long-term motivation for end users to provide their idle processor time to support computationally intensive tasks. We believe that a practical P2P architecture should provide useful service to both clients with high-performance computing needs and contributors of lower-end computing resources. To achieve this, we are designing dual -service architecture for P2P high-performance divide-and conquer computing; we are also experimenting with a prototype implementation. Our proposed architecture incorporates a master server, utilizes dual satellite servers, and operates on the Internet in a dynamically changing large configuration of lower-end nodes provided by volunteer contributors. A dual satellite server comprises a high-performance computing engine and a lower-end contributor service engine. The computing engine provides generic support for divide and conquer computations. The service engine is intended to provide free useful HTTP-based services to contributors of lower-end computing resources. Our proposed architecture is complementary to and accessible from computational grids, such as Globus, Legion, and Condor. Grids provide remote access to existing higher-end computing resources; in contrast, our goal is to utilize idle processor time of lower-end Internet nodes. Our project is focused on a generic divide and conquer paradigm and on mobile applications of this paradigm that can operate on a loose and ever changing pool of lower-end Internet nodes.
Data Compression for Maskless Lithography Systems: Architecture, Algorithms and Implementation
2008-05-19
Data Compression for Maskless Lithography Systems: Architecture, Algorithms and Implementation Vito Dai Electrical Engineering and Computer Sciences...servers or to redistribute to lists, requires prior specific permission. Data Compression for Maskless Lithography Systems: Architecture, Algorithms and...for Maskless Lithography Systems: Architecture, Algorithms and Implementation Copyright 2008 by Vito Dai 1 Abstract Data Compression for Maskless
Autonomic Computing for Spacecraft Ground Systems
NASA Technical Reports Server (NTRS)
Li, Zhenping; Savkli, Cetin; Jones, Lori
2007-01-01
Autonomic computing for spacecraft ground systems increases the system reliability and reduces the cost of spacecraft operations and software maintenance. In this paper, we present an autonomic computing solution for spacecraft ground systems at NASA Goddard Space Flight Center (GSFC), which consists of an open standard for a message oriented architecture referred to as the GMSEC architecture (Goddard Mission Services Evolution Center), and an autonomic computing tool, the Criteria Action Table (CAT). This solution has been used in many upgraded ground systems for NASA 's missions, and provides a framework for developing solutions with higher autonomic maturity.
Traffic information computing platform for big data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Duan, Zongtao, E-mail: ztduan@chd.edu.cn; Li, Ying, E-mail: ztduan@chd.edu.cn; Zheng, Xibin, E-mail: ztduan@chd.edu.cn
Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.
NASA Astrophysics Data System (ADS)
Tramm, John R.; Gunow, Geoffrey; He, Tim; Smith, Kord S.; Forget, Benoit; Siegel, Andrew R.
2016-05-01
In this study we present and analyze a formulation of the 3D Method of Characteristics (MOC) technique applied to the simulation of full core nuclear reactors. Key features of the algorithm include a task-based parallelism model that allows independent MOC tracks to be assigned to threads dynamically, ensuring load balancing, and a wide vectorizable inner loop that takes advantage of modern SIMD computer architectures. The algorithm is implemented in a set of highly optimized proxy applications in order to investigate its performance characteristics on CPU, GPU, and Intel Xeon Phi architectures. Speed, power, and hardware cost efficiencies are compared. Additionally, performance bottlenecks are identified for each architecture in order to determine the prospects for continued scalability of the algorithm on next generation HPC architectures.
Dynamic array processing for computationally intensive expert systems in CLIPS
NASA Technical Reports Server (NTRS)
Athavale, N. N.; Ragade, R. K.; Fenske, T. E.; Cassaro, M. A.
1990-01-01
This paper puts forth an architecture for implementing a loop for advanced data structure of arrays in CLIPS. An attempt is made to use multi-field variables in such an architecture to process a set of data during the decision making cycle. Also, current limitations on the expert system shells are discussed in brief in this paper. The resulting architecture is designed to circumvent the current limitations set by the expert system shell and also by the operating environment. Such advanced data structures are needed for tightly coupling symbolic and numeric computation modules.
A model for architectural comparison
NASA Astrophysics Data System (ADS)
Ho, Sam; Snyder, Larry
1988-04-01
Recently, architectures for sequential computers became a topic of much discussion and controversy. At the center of this storm is the Reduced Instruction Set Computer, or RISC, first described at Berkeley in 1980. While the merits of the RISC architecture cannot be ignored, its opponents have tried to do just that, while its proponents have expanded and frequently exaggerated them. This state of affairs has persisted to this day. No attempt is made to settle this controversy, since indeed there is likely no one answer. A qualitative framework is provided for a rational discussion of the issues.
Dual-scale topology optoelectronic processor.
Marsden, G C; Krishnamoorthy, A V; Esener, S C; Lee, S H
1991-12-15
The dual-scale topology optoelectronic processor (D-STOP) is a parallel optoelectronic architecture for matrix algebraic processing. The architecture can be used for matrix-vector multiplication and two types of vector outer product. The computations are performed electronically, which allows multiplication and summation concepts in linear algebra to be generalized to various nonlinear or symbolic operations. This generalization permits the application of D-STOP to many computational problems. The architecture uses a minimum number of optical transmitters, which thereby reduces fabrication requirements while maintaining area-efficient electronics. The necessary optical interconnections are space invariant, minimizing space-bandwidth requirements.
An Object-Oriented Network-Centric Software Architecture for Physical Computing
NASA Astrophysics Data System (ADS)
Palmer, Richard
1997-08-01
Recent developments in object-oriented computer languages and infrastructure such as the Internet, Web browsers, and the like provide an opportunity to define a more productive computational environment for scientific programming that is based more closely on the underlying mathematics describing physics than traditional programming languages such as FORTRAN or C++. In this talk I describe an object-oriented software architecture for representing physical problems that includes classes for such common mathematical objects as geometry, boundary conditions, partial differential and integral equations, discretization and numerical solution methods, etc. In practice, a scientific program written using this architecture looks remarkably like the mathematics used to understand the problem, is typically an order of magnitude smaller than traditional FORTRAN or C++ codes, and hence easier to understand, debug, describe, etc. All objects in this architecture are ``network-enabled,'' which means that components of a software solution to a physical problem can be transparently loaded from anywhere on the Internet or other global network. The architecture is expressed as an ``API,'' or application programmers interface specification, with reference embeddings in Java, Python, and C++. A C++ class library for an early version of this API has been implemented for machines ranging from PC's to the IBM SP2, meaning that phidentical codes run on all architectures.
ERIC Educational Resources Information Center
Hung, Y.-C.
2012-01-01
This paper investigates the impact of combining self explaining (SE) with computer architecture diagrams to help novice students learn assembly language programming. Pre- and post-test scores for the experimental and control groups were compared and subjected to covariance (ANCOVA) statistical analysis. Results indicate that the SE-plus-diagram…
MIT CSAIL and Lincoln Laboratory Task Force Report
2016-08-01
projects have been very diverse, spanning several areas of CSAIL concentration, including robotics, big data analytics , wireless communications...spanning several areas of CSAIL concentration, including robotics, big data analytics , wireless communications, computing architectures and...to machine learning systems and algorithms, such as recommender systems, and “Big Data ” analytics . Advanced computing architectures broadly refer to
A Model for Minimizing Numeric Function Generator Complexity and Delay
2007-12-01
allow computation of difficult mathematical functions in less time and with less hardware than commonly employed methods. They compute piecewise...Programmable Gate Arrays (FPGAs). The algorithms and estimation techniques apply to various NFG architectures and mathematical functions. This...thesis compares hardware utilization and propagation delay for various NFG architectures, mathematical functions, word widths, and segmentation methods
Usage of Thin-Client/Server Architecture in Computer Aided Education
ERIC Educational Resources Information Center
Cimen, Caghan; Kavurucu, Yusuf; Aydin, Halit
2014-01-01
With the advances of technology, thin-client/server architecture has become popular in multi-user/single network environments. Thin-client is a user terminal in which the user can login to a domain and run programs by connecting to a remote server. Recent developments in network and hardware technologies (cloud computing, virtualization, etc.)…
Optical Computing Based on Neuronal Models
1988-05-01
walking, and cognition are far too complex for existing sequential digital computers. Therefore new architectures, hardware, and algorithms modeled...collective behavior, and iterative processing into optical processing and artificial neurodynamical systems. Another intriguing promise of neural nets is...with architectures, implementations, and programming; and material research s -7- called for. Our future research in neurodynamics will continue to
Using SPEEDES to simulate the blue gene interconnect network
NASA Technical Reports Server (NTRS)
Springer, P.; Upchurch, E.
2003-01-01
JPL and the Center for Advanced Computer Architecture (CACR) is conducting application and simulation analyses of BG/L in order to establish a range of effectiveness for the Blue Gene/L MPP architecture in performing important classes of computations and to determine the design sensitivity of the global interconnect network in support of real world ASCI application execution.
The Use of Metaphors as a Parametric Design Teaching Model: A Case Study
ERIC Educational Resources Information Center
Agirbas, Asli
2018-01-01
Teaching methodologies for parametric design are being researched all over the world, since there is a growing demand for computer programming logic and its fabrication process in architectural education. The computer programming courses in architectural education are usually done in a very short period of time, and so students have no chance to…
NASA Technical Reports Server (NTRS)
Mavriplis, D. J.; Das, Raja; Saltz, Joel; Vermeland, R. E.
1992-01-01
An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made.
Service-Oriented Architecture for NVO and TeraGrid Computing
NASA Technical Reports Server (NTRS)
Jacob, Joseph; Miller, Craig; Williams, Roy; Steenberg, Conrad; Graham, Matthew
2008-01-01
The National Virtual Observatory (NVO) Extensible Secure Scalable Service Infrastructure (NESSSI) is a Web service architecture and software framework that enables Web-based astronomical data publishing and processing on grid computers such as the National Science Foundation's TeraGrid. Characteristics of this architecture include the following: (1) Services are created, managed, and upgraded by their developers, who are trusted users of computing platforms on which the services are deployed. (2) Service jobs can be initiated by means of Java or Python client programs run on a command line or with Web portals. (3) Access is granted within a graduated security scheme in which the size of a job that can be initiated depends on the level of authentication of the user.
A multitasking finite state architecture for computer control of an electric powertrain
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burba, J.C.
1984-01-01
Finite state techniques provide a common design language between the control engineer and the computer engineer for event driven computer control systems. They simplify communication and provide a highly maintainable control system understandable by both. This paper describes the development of a control system for an electric vehicle powertrain utilizing finite state concepts. The basics of finite state automata are provided as a framework to discuss a unique multitasking software architecture developed for this application. The architecture employs conventional time-sliced techniques with task scheduling controlled by a finite state machine representation of the control strategy of the powertrain. The complexitiesmore » of excitation variable sampling in this environment are also considered.« less
NASA Technical Reports Server (NTRS)
Rickard, D. A.; Bodenheimer, R. E.
1976-01-01
Digital computer components which perform two dimensional array logic operations (Tse logic) on binary data arrays are described. The properties of Golay transforms which make them useful in image processing are reviewed, and several architectures for Golay transform processors are presented with emphasis on the skeletonizing algorithm. Conventional logic control units developed for the Golay transform processors are described. One is a unique microprogrammable control unit that uses a microprocessor to control the Tse computer. The remaining control units are based on programmable logic arrays. Performance criteria are established and utilized to compare the various Golay transform machines developed. A critique of Tse logic is presented, and recommendations for additional research are included.
Network architecture test-beds as platforms for ubiquitous computing.
Roscoe, Timothy
2008-10-28
Distributed systems research, and in particular ubiquitous computing, has traditionally assumed the Internet as a basic underlying communications substrate. Recently, however, the networking research community has come to question the fundamental design or 'architecture' of the Internet. This has been led by two observations: first, that the Internet as it stands is now almost impossible to evolve to support new functionality; and second, that modern applications of all kinds now use the Internet rather differently, and frequently implement their own 'overlay' networks above it to work around its perceived deficiencies. In this paper, I discuss recent academic projects to allow disruptive change to the Internet architecture, and also outline a radically different view of networking for ubiquitous computing that such proposals might facilitate.
FPGA-based real-time phase measuring profilometry algorithm design and implementation
NASA Astrophysics Data System (ADS)
Zhan, Guomin; Tang, Hongwei; Zhong, Kai; Li, Zhongwei; Shi, Yusheng
2016-11-01
Phase measuring profilometry (PMP) has been widely used in many fields, like Computer Aided Verification (CAV), Flexible Manufacturing System (FMS) et al. High frame-rate (HFR) real-time vision-based feedback control will be a common demands in near future. However, the instruction time delay in the computer caused by numerous repetitive operations greatly limit the efficiency of data processing. FPGA has the advantages of pipeline architecture and parallel execution, and it fit for handling PMP algorithm. In this paper, we design a fully pipelined hardware architecture for PMP. The functions of hardware architecture includes rectification, phase calculation, phase shifting, and stereo matching. The experiment verified the performance of this method, and the factors that may influence the computation accuracy was analyzed.
NASA Astrophysics Data System (ADS)
Ragan-Kelley, M.; Perez, F.; Granger, B.; Kluyver, T.; Ivanov, P.; Frederic, J.; Bussonnier, M.
2014-12-01
IPython has provided terminal-based tools for interactive computing in Python since 2001. The notebook document format and multi-process architecture introduced in 2011 have expanded the applicable scope of IPython into teaching, presenting, and sharing computational work, in addition to interactive exploration. The new architecture also allows users to work in any language, with implementations in Python, R, Julia, Haskell, and several other languages. The language agnostic parts of IPython have been renamed to Jupyter, to better capture the notion that a cross-language design can encapsulate commonalities present in computational research regardless of the programming language being used. This architecture offers components like the web-based Notebook interface, that supports rich documents that combine code and computational results with text narratives, mathematics, images, video and any media that a modern browser can display. This interface can be used not only in research, but also for publication and education, as notebooks can be converted to a variety of output formats, including HTML and PDF. Recent developments in the Jupyter project include a multi-user environment for hosting notebooks for a class or research group, a live collaboration notebook via Google Docs, and better support for languages other than Python.
OS friendly microprocessor architecture: Hardware level computer security
NASA Astrophysics Data System (ADS)
Jungwirth, Patrick; La Fratta, Patrick
2016-05-01
We present an introduction to the patented OS Friendly Microprocessor Architecture (OSFA) and hardware level computer security. Conventional microprocessors have not tried to balance hardware performance and OS performance at the same time. Conventional microprocessors have depended on the Operating System for computer security and information assurance. The goal of the OS Friendly Architecture is to provide a high performance and secure microprocessor and OS system. We are interested in cyber security, information technology (IT), and SCADA control professionals reviewing the hardware level security features. The OS Friendly Architecture is a switched set of cache memory banks in a pipeline configuration. For light-weight threads, the memory pipeline configuration provides near instantaneous context switching times. The pipelining and parallelism provided by the cache memory pipeline provides for background cache read and write operations while the microprocessor's execution pipeline is running instructions. The cache bank selection controllers provide arbitration to prevent the memory pipeline and microprocessor's execution pipeline from accessing the same cache bank at the same time. This separation allows the cache memory pages to transfer to and from level 1 (L1) caching while the microprocessor pipeline is executing instructions. Computer security operations are implemented in hardware. By extending Unix file permissions bits to each cache memory bank and memory address, the OSFA provides hardware level computer security.
Internet Architecture: Lessons Learned and Looking Forward
2006-12-01
Internet Architecture: Lessons Learned and Looking Forward Geoffrey G. Xie Department of Computer Science Naval Postgraduate School April 2006... Internet architecture. Report Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is...readers are referred there for more information about a specific protocol or concept. 2. Origin of Internet Architecture The Internet is easily
ERIC Educational Resources Information Center
Uwakonye, Obioha; Alagbe, Oluwole; Oluwatayo, Adedapo; Alagbe, Taiye; Alalade, Gbenga
2015-01-01
As a result of globalization of digital technology, intellectual discourse on what constitutes the basic body of architectural knowledge to be imparted to future professionals has been on the increase. This digital revolution has brought to the fore the need to review the already overloaded architectural education curriculum of Nigerian schools of…
Sabne, Amit J.; Sakdhnagool, Putt; Lee, Seyong; ...
2015-07-13
Accelerator-based heterogeneous computing is gaining momentum in the high-performance computing arena. However, the increased complexity of heterogeneous architectures demands more generic, high-level programming models. OpenACC is one such attempt to tackle this problem. Although the abstraction provided by OpenACC offers productivity, it raises questions concerning both functional and performance portability. In this article, the authors propose HeteroIR, a high-level, architecture-independent intermediate representation, to map high-level programming models, such as OpenACC, to heterogeneous architectures. They present a compiler approach that translates OpenACC programs into HeteroIR and accelerator kernels to obtain OpenACC functional portability. They then evaluate the performance portability obtained bymore » OpenACC with their approach on 12 OpenACC programs on Nvidia CUDA, AMD GCN, and Intel Xeon Phi architectures. They study the effects of various compiler optimizations and OpenACC program settings on these architectures to provide insights into the achieved performance portability.« less
The future of computing--new architectures and new technologies.
Warren, P
2004-02-01
All modern computers are designed using the 'von Neumann' architecture and built using silicon transistor technology. Both architecture and technology have been remarkably successful. Yet there are a range of problems for which this conventional architecture is not particularly well adapted, and new architectures are being proposed to solve these problems, in particular based on insight from nature. Transistor technology has enjoyed 50 years of continuing progress. However, the laws of physics dictate that within a relatively short time period this progress will come to an end. New technologies, based on molecular and biological sciences as well as quantum physics, are vying to replace silicon, or at least coexist with it and extend its capability. The paper describes these novel architectures and technologies, places them in the context of the kinds of problems they might help to solve, and predicts their possible manner and time of adoption. Finally it describes some key questions and research problems associated with their use.
Scalable service architecture for providing strong service guarantees
NASA Astrophysics Data System (ADS)
Christin, Nicolas; Liebeherr, Joerg
2002-07-01
For the past decade, a lot of Internet research has been devoted to providing different levels of service to applications. Initial proposals for service differentiation provided strong service guarantees, with strict bounds on delays, loss rates, and throughput, but required high overhead in terms of computational complexity and memory, both of which raise scalability concerns. Recently, the interest has shifted to service architectures with low overhead. However, these newer service architectures only provide weak service guarantees, which do not always address the needs of applications. In this paper, we describe a service architecture that supports strong service guarantees, can be implemented with low computational complexity, and only requires to maintain little state information. A key mechanism of the proposed service architecture is that it addresses scheduling and buffer management in a single algorithm. The presented architecture offers no solution for controlling the amount of traffic that enters the network. Instead, we plan on exploiting feedback mechanisms of TCP congestion control algorithms for the purpose of regulating the traffic entering the network.
GPU-computing in econophysics and statistical physics
NASA Astrophysics Data System (ADS)
Preis, T.
2011-03-01
A recent trend in computer science and related fields is general purpose computing on graphics processing units (GPUs), which can yield impressive performance. With multiple cores connected by high memory bandwidth, today's GPUs offer resources for non-graphics parallel processing. This article provides a brief introduction into the field of GPU computing and includes examples. In particular computationally expensive analyses employed in financial market context are coded on a graphics card architecture which leads to a significant reduction of computing time. In order to demonstrate the wide range of possible applications, a standard model in statistical physics - the Ising model - is ported to a graphics card architecture as well, resulting in large speedup values.
NASA Astrophysics Data System (ADS)
Ford, Eric B.; Dindar, Saleh; Peters, Jorg
2015-08-01
The realism of astrophysical simulations and statistical analyses of astronomical data are set by the available computational resources. Thus, astronomers and astrophysicists are constantly pushing the limits of computational capabilities. For decades, astronomers benefited from massive improvements in computational power that were driven primarily by increasing clock speeds and required relatively little attention to details of the computational hardware. For nearly a decade, increases in computational capabilities have come primarily from increasing the degree of parallelism, rather than increasing clock speeds. Further increases in computational capabilities will likely be led by many-core architectures such as Graphical Processing Units (GPUs) and Intel Xeon Phi. Successfully harnessing these new architectures, requires significantly more understanding of the hardware architecture, cache hierarchy, compiler capabilities and network network characteristics.I will provide an astronomer's overview of the opportunities and challenges provided by modern many-core architectures and elastic cloud computing. The primary goal is to help an astronomical audience understand what types of problems are likely to yield more than order of magnitude speed-ups and which problems are unlikely to parallelize sufficiently efficiently to be worth the development time and/or costs.I will draw on my experience leading a team in developing the Swarm-NG library for parallel integration of large ensembles of small n-body systems on GPUs, as well as several smaller software projects. I will share lessons learned from collaborating with computer scientists, including both technical and soft skills. Finally, I will discuss the challenges of training the next generation of astronomers to be proficient in this new era of high-performance computing, drawing on experience teaching a graduate class on High-Performance Scientific Computing for Astrophysics and organizing a 2014 advanced summer school on Bayesian Computing for Astronomical Data Analysis with support of the Penn State Center for Astrostatistics and Institute for CyberScience.
Power Efficient Hardware Architecture of SHA-1 Algorithm for Trusted Mobile Computing
NASA Astrophysics Data System (ADS)
Kim, Mooseop; Ryou, Jaecheol
The Trusted Mobile Platform (TMP) is developed and promoted by the Trusted Computing Group (TCG), which is an industry standard body to enhance the security of the mobile computing environment. The built-in SHA-1 engine in TMP is one of the most important circuit blocks and contributes the performance of the whole platform because it is used as key primitives supporting platform integrity and command authentication. Mobile platforms have very stringent limitations with respect to available power, physical circuit area, and cost. Therefore special architecture and design methods for low power SHA-1 circuit are required. In this paper, we present a novel and efficient hardware architecture of low power SHA-1 design for TMP. Our low power SHA-1 hardware can compute 512-bit data block using less than 7,000 gates and has a power consumption about 1.1 mA on a 0.25μm CMOS process.
An Evaluation of Architectural Platforms for Parallel Navier-Stokes Computations
NASA Technical Reports Server (NTRS)
Jayasimha, D. N.; Hayder, M. E.; Pillay, S. K.
1996-01-01
We study the computational, communication, and scalability characteristics of a computational fluid dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architecture platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), and distributed memory multiprocessors with different topologies - the IBM SP and the Cray T3D. We investigate the impact of various networks connecting the cluster of workstations on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.
Parallelizing Navier-Stokes Computations on a Variety of Architectural Platforms
NASA Technical Reports Server (NTRS)
Jayasimha, D. N.; Hayder, M. E.; Pillay, S. K.
1997-01-01
We study the computational, communication, and scalability characteristics of a Computational Fluid Dynamics application, which solves the time accurate flow field of a jet using the compressible Navier-Stokes equations, on a variety of parallel architectural platforms. The platforms chosen for this study are a cluster of workstations (the LACE experimental testbed at NASA Lewis), a shared memory multiprocessor (the Cray YMP), distributed memory multiprocessors with different topologies-the IBM SP and the Cray T3D. We investigate the impact of various networks, connecting the cluster of workstations, on the performance of the application and the overheads induced by popular message passing libraries used for parallelization. The work also highlights the importance of matching the memory bandwidth to the processor speed for good single processor performance. By studying the performance of an application on a variety of architectures, we are able to point out the strengths and weaknesses of each of the example computing platforms.
Performance Analysis of Distributed Object-Oriented Applications
NASA Technical Reports Server (NTRS)
Schoeffler, James D.
1998-01-01
The purpose of this research was to evaluate the efficiency of a distributed simulation architecture which creates individual modules which are made self-scheduling through the use of a message-based communication system used for requesting input data from another module which is the source of that data. To make the architecture as general as possible, the message-based communication architecture was implemented using standard remote object architectures (Common Object Request Broker Architecture (CORBA) and/or Distributed Component Object Model (DCOM)). A series of experiments were run in which different systems are distributed in a variety of ways across multiple computers and the performance evaluated. The experiments were duplicated in each case so that the overhead due to message communication and data transmission can be separated from the time required to actually perform the computational update of a module each iteration. The software used to distribute the modules across multiple computers was developed in the first year of the current grant and was modified considerably to add a message-based communication scheme supported by the DCOM distributed object architecture. The resulting performance was analyzed using a model created during the first year of this grant which predicts the overhead due to CORBA and DCOM remote procedure calls and includes the effects of data passed to and from the remote objects. A report covering the distributed simulation software and the results of the performance experiments has been submitted separately. The above report also discusses possible future work to apply the methodology to dynamically distribute the simulation modules so as to minimize overall computation time.
Parallel algorithms for mapping pipelined and parallel computations
NASA Technical Reports Server (NTRS)
Nicol, David M.
1988-01-01
Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.
Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations
NASA Technical Reports Server (NTRS)
Oliker, Leonid; Carter, Jonathan; Shalf, John; Skinner, David; Ethier, Stephane; Biswas, Rupak; Djomehri, Jahed; VanderWijngaart, Rob
2003-01-01
The growing gap between sustained and peak performance for scientific applications has become a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to bridge this gap for a significant number of computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines a full spectrum of low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks using some simple optimizations. Finally, we evaluate the perfor- mance of several numerical codes from key scientific computing domains. Overall results demonstrate that the SX6 achieves high performance on a large fraction of our application suite and in many cases significantly outperforms the RISC-based architectures. However, certain classes of applications are not easily amenable to vectorization and would likely require extensive reengineering of both algorithm and implementation to utilize the SX6 effectively.
Programming for 1.6 Millon cores: Early experiences with IBM's BG/Q SMP architecture
NASA Astrophysics Data System (ADS)
Glosli, James
2013-03-01
With the stall in clock cycle improvements a decade ago, the drive for computational performance has continues along a path of increasing core counts on a processor. The multi-core evolution has been expressed in both a symmetric multi processor (SMP) architecture and cpu/GPU architecture. Debates rage in the high performance computing (HPC) community which architecture best serves HPC. In this talk I will not attempt to resolve that debate but perhaps fuel it. I will discuss the experience of exploiting Sequoia, a 98304 node IBM Blue Gene/Q SMP at Lawrence Livermore National Laboratory. The advantages and challenges of leveraging the computational power BG/Q will be detailed through the discussion of two applications. The first application is a Molecular Dynamics code called ddcMD. This is a code developed over the last decade at LLNL and ported to BG/Q. The second application is a cardiac modeling code called Cardioid. This is a code that was recently designed and developed at LLNL to exploit the fine scale parallelism of BG/Q's SMP architecture. Through the lenses of these efforts I'll illustrate the need to rethink how we express and implement our computational approaches. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.
Parallel compression/decompression-based datapath architecture for multibeam mask writers
NASA Astrophysics Data System (ADS)
Chaudhary, Narendra; Savari, Serap A.
2017-06-01
Multibeam electron beam systems will be used in the future for mask writing and for complimentary lithography. The major challenges of the multibeam systems are in meeting throughput requirements and in handling the large data volumes associated with writing grayscale data on the wafer. In terms of future communications and computational requirements Amdahl's Law suggests that a simple increase of computation power and parallelism may not be a sustainable solution. We propose a parallel data compression algorithm to exploit the sparsity of mask data and a grayscale video-like representation of data. To improve the communication and computational efficiency of these systems at the write time we propose an alternate datapath architecture partly motivated by multibeam direct write lithography and partly motivated by the circuit testing literature, where parallel decompression reduces clock cycles. We explain a deflection plate architecture inspired by NuFlare Technology's multibeam mask writing system and how our datapath architecture can be easily added to it to improve performance.
Parallel compression/decompression-based datapath architecture for multibeam mask writers
NASA Astrophysics Data System (ADS)
Chaudhary, Narendra; Savari, Serap A.
2017-10-01
Multibeam electron beam systems will be used in the future for mask writing and for complementary lithography. The major challenges of the multibeam systems are in meeting throughput requirements and in handling the large data volumes associated with writing grayscale data on the wafer. In terms of future communications and computational requirements, Amdahl's law suggests that a simple increase of computation power and parallelism may not be a sustainable solution. We propose a parallel data compression algorithm to exploit the sparsity of mask data and a grayscale video-like representation of data. To improve the communication and computational efficiency of these systems at the write time, we propose an alternate datapath architecture partly motivated by multibeam direct-write lithography and partly motivated by the circuit testing literature, where parallel decompression reduces clock cycles. We explain a deflection plate architecture inspired by NuFlare Technology's multibeam mask writing system and how our datapath architecture can be easily added to it to improve performance.
Chessa, Manuela; Bianchi, Valentina; Zampetti, Massimo; Sabatini, Silvio P; Solari, Fabio
2012-01-01
The intrinsic parallelism of visual neural architectures based on distributed hierarchical layers is well suited to be implemented on the multi-core architectures of modern graphics cards. The design strategies that allow us to optimally take advantage of such parallelism, in order to efficiently map on GPU the hierarchy of layers and the canonical neural computations, are proposed. Specifically, the advantages of a cortical map-like representation of the data are exploited. Moreover, a GPU implementation of a novel neural architecture for the computation of binocular disparity from stereo image pairs, based on populations of binocular energy neurons, is presented. The implemented neural model achieves good performances in terms of reliability of the disparity estimates and a near real-time execution speed, thus demonstrating the effectiveness of the devised design strategies. The proposed approach is valid in general, since the neural building blocks we implemented are a common basis for the modeling of visual neural functionalities.
Virtual Business Operating Environment in the Cloud: Conceptual Architecture and Challenges
NASA Astrophysics Data System (ADS)
Nezhad, Hamid R. Motahari; Stephenson, Bryan; Singhal, Sharad; Castellanos, Malu
Advances in service oriented architecture (SOA) have brought us close to the once imaginary vision of establishing and running a virtual business, a business in which most or all of its business functions are outsourced to online services. Cloud computing offers a realization of SOA in which IT resources are offered as services that are more affordable, flexible and attractive to businesses. In this paper, we briefly study advances in cloud computing, and discuss the benefits of using cloud services for businesses and trade-offs that they have to consider. We then present 1) a layered architecture for the virtual business, and 2) a conceptual architecture for a virtual business operating environment. We discuss the opportunities and research challenges that are ahead of us in realizing the technical components of this conceptual architecture. We conclude by giving the outlook and impact of cloud services on both large and small businesses.
Strategies for concurrent processing of complex algorithms in data driven architectures
NASA Technical Reports Server (NTRS)
Stoughton, John W.; Mielke, Roland R.
1987-01-01
The results of ongoing research directed at developing a graph theoretical model for describing data and control flow associated with the execution of large grained algorithms in a spatial distributed computer environment is presented. This model is identified by the acronym ATAMM (Algorithm/Architecture Mapping Model). The purpose of such a model is to provide a basis for establishing rules for relating an algorithm to its execution in a multiprocessor environment. Specifications derived from the model lead directly to the description of a data flow architecture which is a consequence of the inherent behavior of the data and control flow described by the model. The purpose of the ATAMM based architecture is to optimize computational concurrency in the multiprocessor environment and to provide an analytical basis for performance evaluation. The ATAMM model and architecture specifications are demonstrated on a prototype system for concept validation.
A "Language Lab" for Architectural Design.
ERIC Educational Resources Information Center
Mackenzie, Arch; And Others
This paper discusses a "language lab" strategy in which traditional studio learning may be supplemented by language lessons using computer graphics techniques to teach architectural grammar, a body of elements and principles that govern the design of buildings belonging to a particular architectural theory or style. Two methods of…
NASA Astrophysics Data System (ADS)
Shi, X.
2015-12-01
As NSF indicated - "Theory and experimentation have for centuries been regarded as two fundamental pillars of science. It is now widely recognized that computational and data-enabled science forms a critical third pillar." Geocomputation is the third pillar of GIScience and geosciences. With the exponential growth of geodata, the challenge of scalable and high performance computing for big data analytics become urgent because many research activities are constrained by the inability of software or tool that even could not complete the computation process. Heterogeneous geodata integration and analytics obviously magnify the complexity and operational time frame. Many large-scale geospatial problems may be not processable at all if the computer system does not have sufficient memory or computational power. Emerging computer architectures, such as Intel's Many Integrated Core (MIC) Architecture and Graphics Processing Unit (GPU), and advanced computing technologies provide promising solutions to employ massive parallelism and hardware resources to achieve scalability and high performance for data intensive computing over large spatiotemporal and social media data. Exploring novel algorithms and deploying the solutions in massively parallel computing environment to achieve the capability for scalable data processing and analytics over large-scale, complex, and heterogeneous geodata with consistent quality and high-performance has been the central theme of our research team in the Department of Geosciences at the University of Arkansas (UARK). New multi-core architectures combined with application accelerators hold the promise to achieve scalability and high performance by exploiting task and data levels of parallelism that are not supported by the conventional computing systems. Such a parallel or distributed computing environment is particularly suitable for large-scale geocomputation over big data as proved by our prior works, while the potential of such advanced infrastructure remains unexplored in this domain. Within this presentation, our prior and on-going initiatives will be summarized to exemplify how we exploit multicore CPUs, GPUs, and MICs, and clusters of CPUs, GPUs and MICs, to accelerate geocomputation in different applications.
PNNLs Data Intensive Computing research battles Homeland Security threats
David Thurman; Joe Kielman; Katherine Wolf; David Atkinson
2018-05-11
The Pacific Northwest National Laboratorys (PNNL's) approach to data intensive computing (DIC) is focused on three key research areas: hybrid hardware architecture, software architectures, and analytic algorithms. Advancements in these areas will help to address, and solve, DIC issues associated with capturing, managing, analyzing and understanding, in near real time, data at volumes and rates that push the frontiers of current technologies.
Design and Training of Limited-Interconnect Architectures
1991-07-16
and signal processing. Neuromorphic (brain like) models, allow an alternative for achieving real-time operation tor such tasks, while having a...compact and robust architecture. Neuromorphic models consist of interconnections of simple computational nodes. In this approach, each node computes a...operational performance. I1. Research Objectives The research objectives were: 1. Development of on- chip local training rules specifically designed for
Pipelined CPU Design with FPGA in Teaching Computer Architecture
ERIC Educational Resources Information Center
Lee, Jong Hyuk; Lee, Seung Eun; Yu, Heon Chang; Suh, Taeweon
2012-01-01
This paper presents a pipelined CPU design project with a field programmable gate array (FPGA) system in a computer architecture course. The class project is a five-stage pipelined 32-bit MIPS design with experiments on the Altera DE2 board. For proper scheduling, milestones were set every one or two weeks to help students complete the project on…
PNNL pushing scientific discovery through data intensive computing breakthroughs
Deborah Gracio; David Koppenaal; Ruby Leung
2018-05-18
The Pacific Northwest National Laboratory's approach to data intensive computing (DIC) is focused on three key research areas: hybrid hardware architectures, software architectures, and analytic algorithms. Advancements in these areas will help to address, and solve, DIC issues associated with capturing, managing, analyzing and understanding, in near real time, data at volumes and rates that push the frontiers of current technologies.
Fault tolerant computer control for a Maglev transportation system
NASA Technical Reports Server (NTRS)
Lala, Jaynarayan H.; Nagle, Gail A.; Anagnostopoulos, George
1994-01-01
Magnetically levitated (Maglev) vehicles operating on dedicated guideways at speeds of 500 km/hr are an emerging transportation alternative to short-haul air and high-speed rail. They have the potential to offer a service significantly more dependable than air and with less operating cost than both air and high-speed rail. Maglev transportation derives these benefits by using magnetic forces to suspend a vehicle 8 to 200 mm above the guideway. Magnetic forces are also used for propulsion and guidance. The combination of high speed, short headways, stringent ride quality requirements, and a distributed offboard propulsion system necessitates high levels of automation for the Maglev control and operation. Very high levels of safety and availability will be required for the Maglev control system. This paper describes the mission scenario, functional requirements, and dependability and performance requirements of the Maglev command, control, and communications system. A distributed hierarchical architecture consisting of vehicle on-board computers, wayside zone computers, a central computer facility, and communication links between these entities was synthesized to meet the functional and dependability requirements on the maglev. Two variations of the basic architecture are described: the Smart Vehicle Architecture (SVA) and the Zone Control Architecture (ZCA). Preliminary dependability modeling results are also presented.
Quantum error correction in crossbar architectures
NASA Astrophysics Data System (ADS)
Helsen, Jonas; Steudtner, Mark; Veldhorst, Menno; Wehner, Stephanie
2018-07-01
A central challenge for the scaling of quantum computing systems is the need to control all qubits in the system without a large overhead. A solution for this problem in classical computing comes in the form of so-called crossbar architectures. Recently we made a proposal for a large-scale quantum processor (Li et al arXiv:1711.03807 (2017)) to be implemented in silicon quantum dots. This system features a crossbar control architecture which limits parallel single-qubit control, but allows the scheme to overcome control scaling issues that form a major hurdle to large-scale quantum computing systems. In this work, we develop a language that makes it possible to easily map quantum circuits to crossbar systems, taking into account their architecture and control limitations. Using this language we show how to map well known quantum error correction codes such as the planar surface and color codes in this limited control setting with only a small overhead in time. We analyze the logical error behavior of this surface code mapping for estimated experimental parameters of the crossbar system and conclude that logical error suppression to a level useful for real quantum computation is feasible.
Robust Software Architecture for Robots
NASA Technical Reports Server (NTRS)
Aghazanian, Hrand; Baumgartner, Eric; Garrett, Michael
2009-01-01
Robust Real-Time Reconfigurable Robotics Software Architecture (R4SA) is the name of both a software architecture and software that embodies the architecture. The architecture was conceived in the spirit of current practice in designing modular, hard, realtime aerospace systems. The architecture facilitates the integration of new sensory, motor, and control software modules into the software of a given robotic system. R4SA was developed for initial application aboard exploratory mobile robots on Mars, but is adaptable to terrestrial robotic systems, real-time embedded computing systems in general, and robotic toys.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less
2006-07-14
MINDS: Architecture & Design Technical Report Department of Computer Science and Engineering University of Minnesota 4-192 EECS Building 200 Union...Street SE Minneapolis, MN 55455-0159 USA TR 06-022 MINDS: Architecture & Design Varun Chandola, Eric Eilertson, Levent Ertoz, Gyorgy Simon, and Vipin...REPORT DATE 14 JUL 2006 2. REPORT TYPE 3. DATES COVERED 00-07-2006 to 00-07-2006 4. TITLE AND SUBTITLE MINDS: Architecture & Design 5a
VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures
Moreland, Kenneth; Sewell, Christopher; Usher, William; ...
2016-05-09
Here, one of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.
VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures
Moreland, Kenneth; Sewell, Christopher; Usher, William; ...
2016-05-09
Execution on massively threaded processors is one of the most critical challenges for high-performance computing (HPC) scientific visualization. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Moreover, our current production scientific visualization software is not designed for these new types of architectures. In order to address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.
The Architecture of Information at Plateau Beaubourg
ERIC Educational Resources Information Center
Branda, Ewan Edward
2012-01-01
During the course of the 1960s, computers and information networks made their appearance in the public imagination. To architects on the cusp of architecture's postmodern turn, information technology offered new forms, metaphors, and techniques by which modern architecture's technological and utopian basis could be reasserted. Yet by the end of…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-15
... design features associated with the architecture and connectivity capabilities of the airplane's computer... novel or unusual design features: digital systems architecture composed of several connected networks. The architecture and network configuration may be used for, or interfaced with, a diverse set of...
2014-11-01
Integrated Cognitive-neuroscience Architectures for Understanding Sensemaking (ICArUS): Phase 1 Test and Evaluation Development Guide Craig...Self-initiated sensemaking ........................................................................................... 19 Feature Vector Format: Tasks...The Integrated Cognitive-neuroscience Architectures for Understanding Sensemaking (ICArUS) Program aimed to build computational cognitive
Multi-level Hierarchical Poly Tree computer architectures
NASA Technical Reports Server (NTRS)
Padovan, Joe; Gute, Doug
1990-01-01
Based on the concept of hierarchical substructuring, this paper develops an optimal multi-level Hierarchical Poly Tree (HPT) parallel computer architecture scheme which is applicable to the solution of finite element and difference simulations. Emphasis is given to minimizing computational effort, in-core/out-of-core memory requirements, and the data transfer between processors. In addition, a simplified communications network that reduces the number of I/O channels between processors is presented. HPT configurations that yield optimal superlinearities are also demonstrated. Moreover, to generalize the scope of applicability, special attention is given to developing: (1) multi-level reduction trees which provide an orderly/optimal procedure by which model densification/simplification can be achieved, as well as (2) methodologies enabling processor grading that yields architectures with varying types of multi-level granularity.
Benchmarking high performance computing architectures with CMS’ skeleton framework
NASA Astrophysics Data System (ADS)
Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.
2017-10-01
In 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta, Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.
FFT Computation with Systolic Arrays, A New Architecture
NASA Technical Reports Server (NTRS)
Boriakoff, Valentin
1994-01-01
The use of the Cooley-Tukey algorithm for computing the l-d FFT lends itself to a particular matrix factorization which suggests direct implementation by linearly-connected systolic arrays. Here we present a new systolic architecture that embodies this algorithm. This implementation requires a smaller number of processors and a smaller number of memory cells than other recent implementations, as well as having all the advantages of systolic arrays. For the implementation of the decimation-in-frequency case, word-serial data input allows continuous real-time operation without the need of a serial-to-parallel conversion device. No control or data stream switching is necessary. Computer simulation of this architecture was done in the context of a 1024 point DFT with a fixed point processor, and CMOS processor implementation has started.
NETRA: A parallel architecture for integrated vision systems. 1: Architecture and organization
NASA Technical Reports Server (NTRS)
Choudhary, Alok N.; Patel, Janak H.; Ahuja, Narendra
1989-01-01
Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is considered to be a system that uses vision algorithms from all levels of processing for a high level application (such as object recognition). A model of computation is presented for parallel processing for an IVS. Using the model, desired features and capabilities of a parallel architecture suitable for IVSs are derived. Then a multiprocessor architecture (called NETRA) is presented. This architecture is highly flexible without the use of complex interconnection schemes. The topology of NETRA is recursively defined and hence is easily scalable from small to large systems. Homogeneity of NETRA permits fault tolerance and graceful degradation under faults. It is a recursively defined tree-type hierarchical architecture where each of the leaf nodes consists of a cluster of processors connected with a programmable crossbar with selective broadcast capability to provide for desired flexibility. A qualitative evaluation of NETRA is presented. Then general schemes are described to map parallel algorithms onto NETRA. Algorithms are classified according to their communication requirements for parallel processing. An extensive analysis of inter-cluster communication strategies in NETRA is presented, and parameters affecting performance of parallel algorithms when mapped on NETRA are discussed. Finally, a methodology to evaluate performance of algorithms on NETRA is described.
The Nebula Standard Computer Architecture,
good target for high level languages, the designers also adopted a visibility approach in architecture design that provides more freedom for the hardware implementor while still maintaining software portability. (Author)
NASA Astrophysics Data System (ADS)
Nishiura, Daisuke; Furuichi, Mikito; Sakaguchi, Hide
2015-09-01
The computational performance of a smoothed particle hydrodynamics (SPH) simulation is investigated for three types of current shared-memory parallel computer devices: many integrated core (MIC) processors, graphics processing units (GPUs), and multi-core CPUs. We are especially interested in efficient shared-memory allocation methods for each chipset, because the efficient data access patterns differ between compute unified device architecture (CUDA) programming for GPUs and OpenMP programming for MIC processors and multi-core CPUs. We first introduce several parallel implementation techniques for the SPH code, and then examine these on our target computer architectures to determine the most effective algorithms for each processor unit. In addition, we evaluate the effective computing performance and power efficiency of the SPH simulation on each architecture, as these are critical metrics for overall performance in a multi-device environment. In our benchmark test, the GPU is found to produce the best arithmetic performance as a standalone device unit, and gives the most efficient power consumption. The multi-core CPU obtains the most effective computing performance. The computational speed of the MIC processor on Xeon Phi approached that of two Xeon CPUs. This indicates that using MICs is an attractive choice for existing SPH codes on multi-core CPUs parallelized by OpenMP, as it gains computational acceleration without the need for significant changes to the source code.
GPU and APU computations of Finite Time Lyapunov Exponent fields
NASA Astrophysics Data System (ADS)
Conti, Christian; Rossinelli, Diego; Koumoutsakos, Petros
2012-03-01
We present GPU and APU accelerated computations of Finite-Time Lyapunov Exponent (FTLE) fields. The calculation of FTLEs is a computationally intensive process, as in order to obtain the sharp ridges associated with the Lagrangian Coherent Structures an extensive resampling of the flow field is required. The computational performance of this resampling is limited by the memory bandwidth of the underlying computer architecture. The present technique harnesses data-parallel execution of many-core architectures and relies on fast and accurate evaluations of moment conserving functions for the mesh to particle interpolations. We demonstrate how the computation of FTLEs can be efficiently performed on a GPU and on an APU through OpenCL and we report over one order of magnitude improvements over multi-threaded executions in FTLE computations of bluff body flows.
Benchmarking hardware architecture candidates for the NFIRAOS real-time controller
NASA Astrophysics Data System (ADS)
Smith, Malcolm; Kerley, Dan; Herriot, Glen; Véran, Jean-Pierre
2014-07-01
As a part of the trade study for the Narrow Field Infrared Adaptive Optics System, the adaptive optics system for the Thirty Meter Telescope, we investigated the feasibility of performing real-time control computation using a Linux operating system and Intel Xeon E5 CPUs. We also investigated a Xeon Phi based architecture which allows higher levels of parallelism. This paper summarizes both the CPU based real-time controller architecture and the Xeon Phi based RTC. The Intel Xeon E5 CPU solution meets the requirements and performs the computation for one AO cycle in an average of 767 microseconds. The Xeon Phi solution did not meet the 1200 microsecond time requirement and also suffered from unpredictable execution times. More detailed benchmark results are reported for both architectures.
Optical systolic solutions of linear algebraic equations
NASA Technical Reports Server (NTRS)
Neuman, C. P.; Casasent, D.
1984-01-01
The philosophy and data encoding possible in systolic array optical processor (SAOP) were reviewed. The multitude of linear algebraic operations achievable on this architecture is examined. These operations include such linear algebraic algorithms as: matrix-decomposition, direct and indirect solutions, implicit and explicit methods for partial differential equations, eigenvalue and eigenvector calculations, and singular value decomposition. This architecture can be utilized to realize general techniques for solving matrix linear and nonlinear algebraic equations, least mean square error solutions, FIR filters, and nested-loop algorithms for control engineering applications. The data flow and pipelining of operations, design of parallel algorithms and flexible architectures, application of these architectures to computationally intensive physical problems, error source modeling of optical processors, and matching of the computational needs of practical engineering problems to the capabilities of optical processors are emphasized.
Laboratory for Computer Science Progress Report 19, 1 July 1981-30 June 1982.
1984-05-01
Multiprocessor Architectures 202 4. TRIX Operating System 209 5. VLSI Tools 212 ’SYSTEMATIC PROGRAM DEVELOPMENT, 221 1. Introduction 222 2. Specification...exploring distributed operating systems and the architecture of single-user powerful computers that are interconnected by communication networks. The...to now. In particular, we expect to experiment with languages, operating systems , and applications that establish the feasibility of distributed
ERIC Educational Resources Information Center
Soares, S. N.; Wagner, F. R.
2011-01-01
Teaching and Design Workbench (T&D-Bench) is a framework aimed at education and research in the areas of computer architecture and embedded systems. It includes a set of features not found in other educational environments. This set of features is the result of an original combination of design requirements for T&D-Bench: that the…
High-Speed Systolic Array Testbed.
1987-10-01
applications since the concept was introduced by H.T. Kung In 1978. This highly parallel architecture of nearet neighbor data communciation and...must be addressed. For instance, should bit-serial or bit parallei computation be utilized. Does the dynamic range of the candidate applications or...numericai stability of the algorithms used require computations In fixed point and Integer format or the architecturally more complex and slower floating
Karthikeyan, M; Krishnan, S; Pandey, Anil Kumar; Bender, Andreas; Tropsha, Alexander
2008-04-01
We present the application of a Java remote method invocation (RMI) based open source architecture to distributed chemical computing. This architecture was previously employed for distributed data harvesting of chemical information from the Internet via the Google application programming interface (API; ChemXtreme). Due to its open source character and its flexibility, the underlying server/client framework can be quickly adopted to virtually every computational task that can be parallelized. Here, we present the server/client communication framework as well as an application to distributed computing of chemical properties on a large scale (currently the size of PubChem; about 18 million compounds), using both the Marvin toolkit as well as the open source JOELib package. As an application, for this set of compounds, the agreement of log P and TPSA between the packages was compared. Outliers were found to be mostly non-druglike compounds and differences could usually be explained by differences in the underlying algorithms. ChemStar is the first open source distributed chemical computing environment built on Java RMI, which is also easily adaptable to user demands due to its "plug-in architecture". The complete source codes as well as calculated properties along with links to PubChem resources are available on the Internet via a graphical user interface at http://moltable.ncl.res.in/chemstar/.
NASA Astrophysics Data System (ADS)
Acernese, Fausto; Barone, Fabrizio; De Rosa, Rosario; Eleuteri, Antonio; Milano, Leopoldo; Pardi, Silvio; Ricciardi, Iolanda; Russo, Guido
2004-09-01
One of the main requirements of a digital system for the control of interferometric detectors of gravitational waves is the computing power, that is a direct consequence of the increasing complexity of the digital algorithms necessary for the control signals generation. For this specific task many specialized non standard real-time architectures have been developed, often very expensive and difficult to upgrade. On the other hand, such computing power is generally fully available for off-line applications on standard Pc based systems. Therefore, a possible and obvious solution may be provided by the integration of both the real-time and off-line architecture resulting in a hybrid control system architecture based on standards available components, trying to get both the advantages of the perfect data synchronization provided by the real-time systems and by the large computing power available on Pc based systems. Such integration may be provided by the implementation of the link between the two different architectures through the standard Ethernet network, whose data transfer speed is largely increasing in these years, using the TCP/IP, UDP and raw Ethernet protocols. In this paper we describe the architecture of an hybrid Ethernet based real-time control system prototype we implemented in Napoli, discussing its characteristics and performances. Finally we discuss a possible application to the real-time control of a suspended mass of the mode cleaner of the 3m prototype optical interferometer for gravitational wave detection (IDGW-3P) operational in Napoli.
Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik
2017-01-01
This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions. PMID:28208684
Liu, Kui; Wei, Sixiao; Chen, Zhijiang; Jia, Bin; Chen, Genshe; Ling, Haibin; Sheaff, Carolyn; Blasch, Erik
2017-02-12
This paper presents the first attempt at combining Cloud with Graphic Processing Units (GPUs) in a complementary manner within the framework of a real-time high performance computation architecture for the application of detecting and tracking multiple moving targets based on Wide Area Motion Imagery (WAMI). More specifically, the GPU and Cloud Moving Target Tracking (GC-MTT) system applied a front-end web based server to perform the interaction with Hadoop and highly parallelized computation functions based on the Compute Unified Device Architecture (CUDA©). The introduced multiple moving target detection and tracking method can be extended to other applications such as pedestrian tracking, group tracking, and Patterns of Life (PoL) analysis. The cloud and GPUs based computing provides an efficient real-time target recognition and tracking approach as compared to methods when the work flow is applied using only central processing units (CPUs). The simultaneous tracking and recognition results demonstrate that a GC-MTT based approach provides drastically improved tracking with low frame rates over realistic conditions.
Unit cell-based computer-aided manufacturing system for tissue engineering.
Kang, Hyun-Wook; Park, Jeong Hun; Kang, Tae-Yun; Seol, Young-Joon; Cho, Dong-Woo
2012-03-01
Scaffolds play an important role in the regeneration of artificial tissues or organs. A scaffold is a porous structure with a micro-scale inner architecture in the range of several to several hundreds of micrometers. Therefore, computer-aided construction of scaffolds should provide sophisticated functionality for porous structure design and a tool path generation strategy that can achieve micro-scale architecture. In this study, a new unit cell-based computer-aided manufacturing (CAM) system was developed for the automated design and fabrication of a porous structure with micro-scale inner architecture that can be applied to composite tissue regeneration. The CAM system was developed by first defining a data structure for the computing process of a unit cell representing a single pore structure. Next, an algorithm and software were developed and applied to construct porous structures with a single or multiple pore design using solid freeform fabrication technology and a 3D tooth/spine computer-aided design model. We showed that this system is quite feasible for the design and fabrication of a scaffold for tissue engineering.
Flynn, Allen J; Bahulekar, Namita; Boisvert, Peter; Lagoze, Carl; Meng, George; Rampton, James; Friedman, Charles P
2017-01-01
Throughout the world, biomedical knowledge is routinely generated and shared through primary and secondary scientific publications. However, there is too much latency between publication of knowledge and its routine use in practice. To address this latency, what is actionable in scientific publications can be encoded to make it computable. We have created a purpose-built digital library platform to hold, manage, and share actionable, computable knowledge for health called the Knowledge Grid Library. Here we present it with its system architecture.
Concepts and Relations in Neurally Inspired In Situ Concept-Based Computing
van der Velde, Frank
2016-01-01
In situ concept-based computing is based on the notion that conceptual representations in the human brain are “in situ.” In this way, they are grounded in perception and action. Examples are neuronal assemblies, whose connection structures develop over time and are distributed over different brain areas. In situ concepts representations cannot be copied or duplicated because that will disrupt their connection structure, and thus the meaning of these concepts. Higher-level cognitive processes, as found in language and reasoning, can be performed with in situ concepts by embedding them in specialized neurally inspired “blackboards.” The interactions between the in situ concepts and the blackboards form the basis for in situ concept computing architectures. In these architectures, memory (concepts) and processing are interwoven, in contrast with the separation between memory and processing found in Von Neumann architectures. Because the further development of Von Neumann computing (more, faster, yet power limited) is questionable, in situ concept computing might be an alternative for concept-based computing. In situ concept computing will be illustrated with a recently developed BABI reasoning task. Neurorobotics can play an important role in the development of in situ concept computing because of the development of in situ concept representations derived in scenarios as needed for reasoning tasks. Neurorobotics would also benefit from power limited and in situ concept computing. PMID:27242504
Concepts and Relations in Neurally Inspired In Situ Concept-Based Computing.
van der Velde, Frank
2016-01-01
In situ concept-based computing is based on the notion that conceptual representations in the human brain are "in situ." In this way, they are grounded in perception and action. Examples are neuronal assemblies, whose connection structures develop over time and are distributed over different brain areas. In situ concepts representations cannot be copied or duplicated because that will disrupt their connection structure, and thus the meaning of these concepts. Higher-level cognitive processes, as found in language and reasoning, can be performed with in situ concepts by embedding them in specialized neurally inspired "blackboards." The interactions between the in situ concepts and the blackboards form the basis for in situ concept computing architectures. In these architectures, memory (concepts) and processing are interwoven, in contrast with the separation between memory and processing found in Von Neumann architectures. Because the further development of Von Neumann computing (more, faster, yet power limited) is questionable, in situ concept computing might be an alternative for concept-based computing. In situ concept computing will be illustrated with a recently developed BABI reasoning task. Neurorobotics can play an important role in the development of in situ concept computing because of the development of in situ concept representations derived in scenarios as needed for reasoning tasks. Neurorobotics would also benefit from power limited and in situ concept computing.
Heterogeneous real-time computing in radio astronomy
NASA Astrophysics Data System (ADS)
Ford, John M.; Demorest, Paul; Ransom, Scott
2010-07-01
Modern computer architectures suited for general purpose computing are often not the best choice for either I/O-bound or compute-bound problems. Sometimes the best choice is not to choose a single architecture, but to take advantage of the best characteristics of different computer architectures to solve your problems. This paper examines the tradeoffs between using computer systems based on the ubiquitous X86 Central Processing Units (CPU's), Field Programmable Gate Array (FPGA) based signal processors, and Graphical Processing Units (GPU's). We will show how a heterogeneous system can be produced that blends the best of each of these technologies into a real-time signal processing system. FPGA's tightly coupled to analog-to-digital converters connect the instrument to the telescope and supply the first level of computing to the system. These FPGA's are coupled to other FPGA's to continue to provide highly efficient processing power. Data is then packaged up and shipped over fast networks to a cluster of general purpose computers equipped with GPU's, which are used for floating-point intensive computation. Finally, the data is handled by the CPU and written to disk, or further processed. Each of the elements in the system has been chosen for its specific characteristics and the role it can play in creating a system that does the most for the least, in terms of power, space, and money.
NASA Astrophysics Data System (ADS)
Romanchuk, V. A.; Lukashenko, V. V.
2018-05-01
The technique of functioning of a control system by a computing cluster based on neurocomputers is proposed. Particular attention is paid to the method of choosing the structure of the computing cluster due to the fact that the existing methods are not effective because of a specialized hardware base - neurocomputers, which are highly parallel computer devices with an architecture different from the von Neumann architecture. A developed algorithm for choosing the computational structure of a cloud cluster is described, starting from the direction of data transfer in the flow control graph of the program and its adjacency matrix.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Venkata, Manjunath Gorentla; Aderholdt, William F
The pre-exascale systems are expected to have a significant amount of hierarchical and heterogeneous on-node memory, and this trend of system architecture in extreme-scale systems is expected to continue into the exascale era. along with hierarchical-heterogeneous memory, the system typically has a high-performing network ad a compute accelerator. This system architecture is not only effective for running traditional High Performance Computing (HPC) applications (Big-Compute), but also for running data-intensive HPC applications and Big-Data applications. As a consequence, there is a growing desire to have a single system serve the needs of both Big-Compute and Big-Data applications. Though the system architecturemore » supports the convergence of the Big-Compute and Big-Data, the programming models and software layer have yet to evolve to support either hierarchical-heterogeneous memory systems or the convergence. A programming abstraction to address this problem. The programming abstraction is implemented as a software library and runs on pre-exascale and exascale systems supporting current and emerging system architecture. Using distributed data-structures as a central concept, it provides (1) a simple, usable, and portable abstraction for hierarchical-heterogeneous memory and (2) a unified programming abstraction for Big-Compute and Big-Data applications.« less
Importance of balanced architectures in the design of high-performance imaging systems
NASA Astrophysics Data System (ADS)
Sgro, Joseph A.; Stanton, Paul C.
1999-03-01
Imaging systems employed in demanding military and industrial applications, such as automatic target recognition and computer vision, typically require real-time high-performance computing resources. While high- performances computing systems have traditionally relied on proprietary architectures and custom components, recent advances in high performance general-purpose microprocessor technology have produced an abundance of low cost components suitable for use in high-performance computing systems. A common pitfall in the design of high performance imaging system, particularly systems employing scalable multiprocessor architectures, is the failure to balance computational and memory bandwidth. The performance of standard cluster designs, for example, in which several processors share a common memory bus, is typically constrained by memory bandwidth. The symptom characteristic of this problem is failure to the performance of the system to scale as more processors are added. The problem becomes exacerbated if I/O and memory functions share the same bus. The recent introduction of microprocessors with large internal caches and high performance external memory interfaces makes it practical to design high performance imaging system with balanced computational and memory bandwidth. Real word examples of such designs will be presented, along with a discussion of adapting algorithm design to best utilize available memory bandwidth.
Cognitive Computing for Security.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Debenedictis, Erik; Rothganger, Fredrick; Aimone, James Bradley
Final report for Cognitive Computing for Security LDRD 165613. It reports on the development of hybrid of general purpose/ne uromorphic computer architecture, with an emphasis on potential implementation with memristors.
Computer Technology: State of the Art.
ERIC Educational Resources Information Center
Withington, Frederic G.
1981-01-01
Describes the nature of modern general-purpose computer systems, including hardware, semiconductor electronics, microprocessors, computer architecture, input output technology, and system control programs. Seven suggested readings are cited. (FM)
Benchmarking high performance computing architectures with CMS’ skeleton framework
Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.
2017-11-23
Here, in 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta,more » Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.« less
A novel strategy for load balancing of distributed medical applications.
Logeswaran, Rajasvaran; Chen, Li-Choo
2012-04-01
Current trends in medicine, specifically in the electronic handling of medical applications, ranging from digital imaging, paperless hospital administration and electronic medical records, telemedicine, to computer-aided diagnosis, creates a burden on the network. Distributed Service Architectures, such as Intelligent Network (IN), Telecommunication Information Networking Architecture (TINA) and Open Service Access (OSA), are able to meet this new challenge. Distribution enables computational tasks to be spread among multiple processors; hence, performance is an important issue. This paper proposes a novel approach in load balancing, the Random Sender Initiated Algorithm, for distribution of tasks among several nodes sharing the same computational object (CO) instances in Distributed Service Architectures. Simulations illustrate that the proposed algorithm produces better network performance than the benchmark load balancing algorithms-the Random Node Selection Algorithm and the Shortest Queue Algorithm, especially under medium and heavily loaded conditions.
Benchmarking high performance computing architectures with CMS’ skeleton framework
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sexton-Kennedy, E.; Gartung, P.; Jones, C. D.
Here, in 2012 CMS evaluated which underlying concurrency technology would be the best to use for its multi-threaded framework. The available technologies were evaluated on the high throughput computing systems dominating the resources in use at that time. A skeleton framework benchmarking suite that emulates the tasks performed within a CMSSW application was used to select Intel’s Thread Building Block library, based on the measured overheads in both memory and CPU on the different technologies benchmarked. In 2016 CMS will get access to high performance computing resources that use new many core architectures; machines such as Cori Phase 1&2, Theta,more » Mira. Because of this we have revived the 2012 benchmark to test it’s performance and conclusions on these new architectures. This talk will discuss the results of this exercise.« less
Cloud Computing for Mission Design and Operations
NASA Technical Reports Server (NTRS)
Arrieta, Juan; Attiyah, Amy; Beswick, Robert; Gerasimantos, Dimitrios
2012-01-01
The space mission design and operations community already recognizes the value of cloud computing and virtualization. However, natural and valid concerns, like security, privacy, up-time, and vendor lock-in, have prevented a more widespread and expedited adoption into official workflows. In the interest of alleviating these concerns, we propose a series of guidelines for internally deploying a resource-oriented hub of data and algorithms. These guidelines provide a roadmap for implementing an architecture inspired in the cloud computing model: associative, elastic, semantical, interconnected, and adaptive. The architecture can be summarized as exposing data and algorithms as resource-oriented Web services, coordinated via messaging, and running on virtual machines; it is simple, and based on widely adopted standards, protocols, and tools. The architecture may help reduce common sources of complexity intrinsic to data-driven, collaborative interactions and, most importantly, it may provide the means for teams and agencies to evaluate the cloud computing model in their specific context, with minimal infrastructure changes, and before committing to a specific cloud services provider.
Scalable quantum computer architecture with coupled donor-quantum dot qubits
Schenkel, Thomas; Lo, Cheuk Chi; Weis, Christoph; Lyon, Stephen; Tyryshkin, Alexei; Bokor, Jeffrey
2014-08-26
A quantum bit computing architecture includes a plurality of single spin memory donor atoms embedded in a semiconductor layer, a plurality of quantum dots arranged with the semiconductor layer and aligned with the donor atoms, wherein a first voltage applied across at least one pair of the aligned quantum dot and donor atom controls a donor-quantum dot coupling. A method of performing quantum computing in a scalable architecture quantum computing apparatus includes arranging a pattern of single spin memory donor atoms in a semiconductor layer, forming a plurality of quantum dots arranged with the semiconductor layer and aligned with the donor atoms, applying a first voltage across at least one aligned pair of a quantum dot and donor atom to control a donor-quantum dot coupling, and applying a second voltage between one or more quantum dots to control a Heisenberg exchange J coupling between quantum dots and to cause transport of a single spin polarized electron between quantum dots.
Massively parallel algorithms for real-time wavefront control of a dense adaptive optics system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fijany, A.; Milman, M.; Redding, D.
1994-12-31
In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. The authors have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although, this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. They develop a novel algorithm,more » designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, this algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures. The authors also discuss two massively parallel, algorithmically specialized, architectures for low-cost and optimal implementation of the Fast Invariant Imbedding algorithm.« less
The role of architecture and ontology for interoperability.
Blobel, Bernd; González, Carolina; Oemig, Frank; Lopéz, Diego; Nykänen, Pirkko; Ruotsalainen, Pekka
2010-01-01
Turning from organization-centric to process-controlled or even to personalized approaches, advanced healthcare settings have to meet special interoperability challenges. eHealth and pHealth solutions must assure interoperability between actors cooperating to achieve common business objectives. Hereby, the interoperability chain also includes individually tailored technical systems, but also sensors and actuators. For enabling corresponding pervasive computing and even autonomic computing, individualized systems have to be based on an architecture framework covering many domains, scientifically managed by specialized disciplines using their specific ontologies in a formalized way. Therefore, interoperability has to advance from a communication protocol to an architecture-centric approach mastering ontology coordination challenges.
NASA Astrophysics Data System (ADS)
Titov, A. G.; Okladnikov, I. G.; Gordov, E. P.
2017-11-01
The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.
An object-oriented software approach for a distributed human tracking motion system
NASA Astrophysics Data System (ADS)
Micucci, Daniela L.
2003-06-01
Tracking is a composite job involving the co-operation of autonomous activities which exploit a complex information model and rely on a distributed architecture. Both information and activities must be classified and related in several dimensions: abstraction levels (what is modelled and how information is processed); topology (where the modelled entities are); time (when entities exist); strategy (why something happens); responsibilities (who is in charge of processing the information). A proper Object-Oriented analysis and design approach leads to a modular architecture where information about conceptual entities is modelled at each abstraction level via classes and intra-level associations, whereas inter-level associations between classes model the abstraction process. Both information and computation are partitioned according to level-specific topological models. They are also placed in a temporal framework modelled by suitable abstractions. Domain-specific strategies control the execution of the computations. Computational components perform both intra-level processing and intra-level information conversion. The paper overviews the phases of the analysis and design process, presents major concepts at each abstraction level, and shows how the resulting design turns into a modular, flexible and adaptive architecture. Finally, the paper sketches how the conceptual architecture can be deployed into a concrete distribute architecture by relying on an experimental framework.
HTMT-class Latency Tolerant Parallel Architecture for Petaflops Scale Computation
NASA Technical Reports Server (NTRS)
Sterling, Thomas; Bergman, Larry
2000-01-01
Computational Aero Sciences and other numeric intensive computation disciplines demand computing throughputs substantially greater than the Teraflops scale systems only now becoming available. The related fields of fluids, structures, thermal, combustion, and dynamic controls are among the interdisciplinary areas that in combination with sufficient resolution and advanced adaptive techniques may force performance requirements towards Petaflops. This will be especially true for compute intensive models such as Navier-Stokes are or when such system models are only part of a larger design optimization computation involving many design points. Yet recent experience with conventional MPP configurations comprising commodity processing and memory components has shown that larger scale frequently results in higher programming difficulty and lower system efficiency. While important advances in system software and algorithms techniques have had some impact on efficiency and programmability for certain classes of problems, in general it is unlikely that software alone will resolve the challenges to higher scalability. As in the past, future generations of high-end computers may require a combination of hardware architecture and system software advances to enable efficient operation at a Petaflops level. The NASA led HTMT project has engaged the talents of a broad interdisciplinary team to develop a new strategy in high-end system architecture to deliver petaflops scale computing in the 2004/5 timeframe. The Hybrid-Technology, MultiThreaded parallel computer architecture incorporates several advanced technologies in combination with an innovative dynamic adaptive scheduling mechanism to provide unprecedented performance and efficiency within practical constraints of cost, complexity, and power consumption. The emerging superconductor Rapid Single Flux Quantum electronics can operate at 100 GHz (the record is 770 GHz) and one percent of the power required by convention semiconductor logic. Wave Division Multiplexing optical communications can approach a peak per fiber bandwidth of 1 Tbps and the new Data Vortex network topology employing this technology can connect tens of thousands of ports providing a bi-section bandwidth on the order of a Petabyte per second with latencies well below 100 nanoseconds, even under heavy loads. Processor-in-Memory (PIM) technology combines logic and memory on the same chip exposing the internal bandwidth of the memory row buffers at low latency. And holographic storage photorefractive storage technologies provide high-density memory with access a thousand times faster than conventional disk technologies. Together these technologies enable a new class of shared memory system architecture with a peak performance in the range of a Petaflops but size and power requirements comparable to today's largest Teraflops scale systems. To achieve high-sustained performance, HTMT combines an advanced multithreading processor architecture with a memory-driven coarse-grained latency management strategy called "percolation", yielding high efficiency while reducing the much of the parallel programming burden. This paper will present the basic system architecture characteristics made possible through this series of advanced technologies and then give a detailed description of the new percolation approach to runtime latency management.
Architecture and the Information Revolution.
ERIC Educational Resources Information Center
Driscoll, Porter; And Others
1982-01-01
Traces how technological changes affect the architecture of the workplace. Traces these effects from the industrial revolution up through the computer revolution. Offers suggested designs for the computerized office of today and tomorrow. (JM)
NASA Technical Reports Server (NTRS)
Chow, Edward T.; Schatzel, Donald V.; Whitaker, William D.; Sterling, Thomas
2008-01-01
A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.
Ravichandiran, Kajeandra; Ravichandiran, Mayoorendra; Oliver, Michele L; Singh, Karan S; McKee, Nancy H; Agur, Anne M R
2009-09-01
Architectural parameters and physiological cross-sectional area (PCSA) are important determinants of muscle function. Extensor carpi radialis longus (ECRL) and brevis (ECRB) are used in muscle transfers; however, their regional architectural differences have not been investigated. The aim of this study is to develop computational algorithms to quantify and compare architectural parameters (fiber bundle length, pennation angle, and volume) and PCSA of ECRL and ECRB. Fiber bundles distributed throughout the volume of ECRL (75+/-20) and ECRB (110+/-30) were digitized in eight formalin embalmed cadaveric specimens. The digitized data was reconstructed in Autodesk Maya with computational algorithms implemented in Python. The mean PCSA and fiber bundle length were significantly different between ECRL and ECRB (p < or = 0.05). Superficial ECRL had significantly longer fiber bundle length than the deep region, whereas the PCSA of superficial ECRB was significantly larger than the deep region. The regional quantification of architectural parameters and PCSA provides a framework for the exploration of partial tendon transfers of ECRL and ECRB.
NASA Technical Reports Server (NTRS)
Harper, R. E.; Alger, L. S.; Babikyan, C. A.; Butler, B. P.; Friend, S. A.; Ganska, R. J.; Lala, J. H.; Masotto, T. K.; Meyer, A. J.; Morton, D. P.
1992-01-01
Digital computing systems needed for Army programs such as the Computer-Aided Low Altitude Helicopter Flight Program and the Armored Systems Modernization (ASM) vehicles may be characterized by high computational throughput and input/output bandwidth, hard real-time response, high reliability and availability, and maintainability, testability, and producibility requirements. In addition, such a system should be affordable to produce, procure, maintain, and upgrade. To address these needs, the Army Fault Tolerant Architecture (AFTA) is being designed and constructed under a three-year program comprised of a conceptual study, detailed design and fabrication, and demonstration and validation phases. Described here are the results of the conceptual study phase of the AFTA development. Given here is an introduction to the AFTA program, its objectives, and key elements of its technical approach. A format is designed for representing mission requirements in a manner suitable for first order AFTA sizing and analysis, followed by a discussion of the current state of mission requirements acquisition for the targeted Army missions. An overview is given of AFTA's architectural theory of operation.
NASA Technical Reports Server (NTRS)
Fischer, James R.; Grosch, Chester; Mcanulty, Michael; Odonnell, John; Storey, Owen
1987-01-01
NASA's Office of Space Science and Applications (OSSA) gave a select group of scientists the opportunity to test and implement their computational algorithms on the Massively Parallel Processor (MPP) located at Goddard Space Flight Center, beginning in late 1985. One year later, the Working Group presented its report, which addressed the following: algorithms, programming languages, architecture, programming environments, the way theory relates, and performance measured. The findings point to a number of demonstrated computational techniques for which the MPP architecture is ideally suited. For example, besides executing much faster on the MPP than on conventional computers, systolic VLSI simulation (where distances are short), lattice simulation, neural network simulation, and image problems were found to be easier to program on the MPP's architecture than on a CYBER 205 or even a VAX. The report also makes technical recommendations covering all aspects of MPP use, and recommendations concerning the future of the MPP and machines based on similar architectures, expansion of the Working Group, and study of the role of future parallel processors for space station, EOS, and the Great Observatories era.
A performance analysis of advanced I/O architectures for PC-based network file servers
NASA Astrophysics Data System (ADS)
Huynh, K. D.; Khoshgoftaar, T. M.
1994-12-01
In the personal computing and workstation environments, more and more I/O adapters are becoming complete functional subsystems that are intelligent enough to handle I/O operations on their own without much intervention from the host processor. The IBM Subsystem Control Block (SCB) architecture has been defined to enhance the potential of these intelligent adapters by defining services and conventions that deliver command information and data to and from the adapters. In recent years, a new storage architecture, the Redundant Array of Independent Disks (RAID), has been quickly gaining acceptance in the world of computing. In this paper, we would like to discuss critical system design issues that are important to the performance of a network file server. We then present a performance analysis of the SCB architecture and disk array technology in typical network file server environments based on personal computers (PCs). One of the key issues investigated in this paper is whether a disk array can outperform a group of disks (of same type, same data capacity, and same cost) operating independently, not in parallel as in a disk array.
Integrating the Apache Big Data Stack with HPC for Big Data
NASA Astrophysics Data System (ADS)
Fox, G. C.; Qiu, J.; Jha, S.
2014-12-01
There is perhaps a broad consensus as to important issues in practical parallel computing as applied to large scale simulations; this is reflected in supercomputer architectures, algorithms, libraries, languages, compilers and best practice for application development. However, the same is not so true for data intensive computing, even though commercially clouds devote much more resources to data analytics than supercomputers devote to simulations. We look at a sample of over 50 big data applications to identify characteristics of data intensive applications and to deduce needed runtime and architectures. We suggest a big data version of the famous Berkeley dwarfs and NAS parallel benchmarks and use these to identify a few key classes of hardware/software architectures. Our analysis builds on combining HPC and ABDS the Apache big data software stack that is well used in modern cloud computing. Initial results on clouds and HPC systems are encouraging. We propose the development of SPIDAL - Scalable Parallel Interoperable Data Analytics Library -- built on system aand data abstractions suggested by the HPC-ABDS architecture. We discuss how it can be used in several application areas including Polar Science.
Implementation and analysis of a Navier-Stokes algorithm on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1988-01-01
The results of the implementation of a Navier-Stokes algorithm on three parallel/vector computers are presented. The object of this research is to determine how well, or poorly, a single numerical algorithm would map onto three different architectures. The algorithm is a compact difference scheme for the solution of the incompressible, two-dimensional, time-dependent Navier-Stokes equations. The computers were chosen so as to encompass a variety of architectures. They are the following: the MPP, an SIMD machine with 16K bit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. The basic comparison is among SIMD instruction parallelism on the MPP, MIMD process parallelism on the Flex/32, and vectorization of a serial code on the Cray/2. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.
Analysis of Disaster Preparedness Planning Measures in DoD Computer Facilities
1993-09-01
city, stae, aod ZP code) 10 Source of Funding Numbers SProgram Element No lProject No ITask No lWork Unit Accesion I 11 Title include security...Computer Disaster Recovery .... 13 a. PC and LAN Lessons Learned . . ..... 13 2. Distributed Architectures . . . .. . 14 3. Backups...amount of expense, but no client problems." (Leeke, 1993, p. 8) 2. Distributed Architectures The majority of operations that were disrupted by the
Computer Architecture for Energy Efficient SFQ
2014-08-27
IBM Corporation (T.J. Watson Research Laboratory) 1101 Kitchawan Road Yorktown Heights, NY 10598 -0000 2 ABSTRACT Number of Papers published in peer...accomplished during this ARO-sponsored project at IBM Research to identify and model an energy efficient SFQ-based computer architecture. The... IBM Windsor Blue (WB), illustrated schematically in Figure 2. The basic building block of WB is a "tile" comprised of a 64-bit arithmetic logic unit
Proactive Fault Tolerance Using Preemptive Migration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Engelmann, Christian; Vallee, Geoffroy R; Naughton, III, Thomas J
2009-01-01
Proactive fault tolerance (FT) in high-performance computing is a concept that prevents compute node failures from impacting running parallel applications by preemptively migrating application parts away from nodes that are about to fail. This paper provides a foundation for proactive FT by defining its architecture and classifying implementation options. This paper further relates prior work to the presented architecture and classification, and discusses the challenges ahead for needed supporting technologies.
Implementation of Virtualization Oriented Architecture: A Healthcare Industry Case Study
NASA Astrophysics Data System (ADS)
Rao, G. Subrahmanya Vrk; Parthasarathi, Jinka; Karthik, Sundararaman; Rao, Gvn Appa; Ganesan, Suresh
This paper presents a Virtualization Oriented Architecture (VOA) and an implementation of VOA for Hridaya - a Telemedicine initiative. Hadoop Compute cloud was established at our labs and jobs which require a massive computing capability such as ECG signal analysis were submitted and the study is presented in this current paper. VOA takes advantage of inexpensive community PCs and provides added advantages such as Fault Tolerance, Scalability, Performance, High Availability.
Optimization of knowledge sharing through multi-forum using cloud computing architecture
NASA Astrophysics Data System (ADS)
Madapusi Vasudevan, Sriram; Sankaran, Srivatsan; Muthuswamy, Shanmugasundaram; Ram, N. Sankar
2011-12-01
Knowledge sharing is done through various knowledge sharing forums which requires multiple logins through multiple browser instances. Here a single Multi-Forum knowledge sharing concept is introduced which requires only one login session which makes user to connect multiple forums and display the data in a single browser window. Also few optimization techniques are introduced here to speed up the access time using cloud computing architecture.
The MIT Alewife Machine: A Large-Scale Distributed-Memory Multiprocessor
1991-06-01
Symposium on Compiler Construction, June 1986. [14] Daniel Gajski , David Kuck, Duncan Lawrie, and Ahmed Saleh. Cedar - A Large Scale Multiprocessor. In...Directory Methods. In Proceedings 17th Annual International Symposium on Computer Architecture, June 1990. [31] G . M. Papadopoulos and D.E. Culler...Monsoon: An Explicit Token-Store Ar- chitecture. In Proceedings 17th Annual International Symposium on Computer Architecture, June 1990. [32] G . F
Design and optimization of a portable LQCD Monte Carlo code using OpenACC
NASA Astrophysics Data System (ADS)
Bonati, Claudio; Coscetti, Simone; D'Elia, Massimo; Mesiti, Michele; Negro, Francesco; Calore, Enrico; Schifano, Sebastiano Fabio; Silvi, Giorgio; Tripiccione, Raffaele
The present panorama of HPC architectures is extremely heterogeneous, ranging from traditional multi-core CPU processors, supporting a wide class of applications but delivering moderate computing performance, to many-core Graphics Processor Units (GPUs), exploiting aggressive data-parallelism and delivering higher performances for streaming computing applications. In this scenario, code portability (and performance portability) become necessary for easy maintainability of applications; this is very relevant in scientific computing where code changes are very frequent, making it tedious and prone to error to keep different code versions aligned. In this work, we present the design and optimization of a state-of-the-art production-level LQCD Monte Carlo application, using the directive-based OpenACC programming model. OpenACC abstracts parallel programming to a descriptive level, relieving programmers from specifying how codes should be mapped onto the target architecture. We describe the implementation of a code fully written in OpenAcc, and show that we are able to target several different architectures, including state-of-the-art traditional CPUs and GPUs, with the same code. We also measure performance, evaluating the computing efficiency of our OpenACC code on several architectures, comparing with GPU-specific implementations and showing that a good level of performance-portability can be reached.
Bioinspired decision architectures containing host and microbiome processing units.
Heyde, K C; Gallagher, P W; Ruder, W C
2016-09-27
Biomimetic robots have been used to explore and explain natural phenomena ranging from the coordination of ants to the locomotion of lizards. Here, we developed a series of decision architectures inspired by the information exchange between a host organism and its microbiome. We first modeled the biochemical exchanges of a population of synthetically engineered E. coli. We then built a physical, differential drive robot that contained an integrated, onboard computer vision system. A relay was established between the simulated population of cells and the robot's microcontroller. By placing the robot within a target-containing a two-dimensional arena, we explored how different aspects of the simulated cells and the robot's microcontroller could be integrated to form hybrid decision architectures. We found that distinct decision architectures allow for us to develop models of computation with specific strengths such as runtime efficiency or minimal memory allocation. Taken together, our hybrid decision architectures provide a new strategy for developing bioinspired control systems that integrate both living and nonliving components.
PIC codes for plasma accelerators on emerging computer architectures (GPUS, Multicore/Manycore CPUS)
NASA Astrophysics Data System (ADS)
Vincenti, Henri
2016-03-01
The advent of exascale computers will enable 3D simulations of a new laser-plasma interaction regimes that were previously out of reach of current Petasale computers. However, the paradigm used to write current PIC codes will have to change in order to fully exploit the potentialities of these new computing architectures. Indeed, achieving Exascale computing facilities in the next decade will be a great challenge in terms of energy consumption and will imply hardware developments directly impacting our way of implementing PIC codes. As data movement (from die to network) is by far the most energy consuming part of an algorithm future computers will tend to increase memory locality at the hardware level and reduce energy consumption related to data movement by using more and more cores on each compute nodes (''fat nodes'') that will have a reduced clock speed to allow for efficient cooling. To compensate for frequency decrease, CPU machine vendors are making use of long SIMD instruction registers that are able to process multiple data with one arithmetic operator in one clock cycle. SIMD register length is expected to double every four years. GPU's also have a reduced clock speed per core and can process Multiple Instructions on Multiple Datas (MIMD). At the software level Particle-In-Cell (PIC) codes will thus have to achieve both good memory locality and vectorization (for Multicore/Manycore CPU) to fully take advantage of these upcoming architectures. In this talk, we present the portable solutions we implemented in our high performance skeleton PIC code PICSAR to both achieve good memory locality and cache reuse as well as good vectorization on SIMD architectures. We also present the portable solutions used to parallelize the Pseudo-sepctral quasi-cylindrical code FBPIC on GPUs using the Numba python compiler.
Integrating Computer Architectures into the Design of High-Performance Controllers
NASA Technical Reports Server (NTRS)
Jacklin, Stephen A.; Leyland, Jane A.; Warmbrodt, William
1986-01-01
Modern control systems must typically perform real-time identification and control, as well as coordinate a host of other activities related to user interaction, on-line graphics, and file management. This paper discusses five global design considerations that are useful to integrate array processor, multimicroprocessor, and host computer system architecture into versatile, high-speed controllers. Such controllers are capable of very high control throughput, and can maintain constant interaction with the non-real-time or user environment. As an application example, the architecture of a high-speed, closed-loop controller used to actively control helicopter vibration will be briefly discussed. Although this system has been designed for use as the controller for real-time rotorcraft dynamics and control studies in a wind-tunnel environment, the control architecture can generally be applied to a wide range of automatic control applications.
An integrative architecture for a sensor-supported trust management system.
Trček, Denis
2012-01-01
Trust plays a key role not only in e-worlds and emerging pervasive computing environments, but also already for millennia in human societies. Trust management solutions that have being around now for some fifteen years were primarily developed for the above mentioned cyber environments and they are typically focused on artificial agents, sensors, etc. However, this paper presents extensions of a new methodology together with architecture for trust management support that is focused on humans and human-like agents. With this methodology and architecture sensors play a crucial role. The architecture presents an already deployable tool for multi and interdisciplinary research in various areas where humans are involved. It provides new ways to obtain an insight into dynamics and evolution of such structures, not only in pervasive computing environments, but also in other important areas like management and decision making support.
Applications of an architecture design and assessment system (ADAS)
NASA Technical Reports Server (NTRS)
Gray, F. Gail; Debrunner, Linda S.; White, Tennis S.
1988-01-01
A new Architecture Design and Assessment System (ADAS) tool package is introduced, and a range of possible applications is illustrated. ADAS was used to evaluate the performance of an advanced fault-tolerant computer architecture in a modern flight control application. Bottlenecks were identified and possible solutions suggested. The tool was also used to inject faults into the architecture and evaluate the synchronization algorithm, and improvements are suggested. Finally, ADAS was used as a front end research tool to aid in the design of reconfiguration algorithms in a distributed array architecture.
Rebooting Computers as Learning Machines
DeBenedictis, Erik P.
2016-06-13
Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.
ICASE Computer Science Program
NASA Technical Reports Server (NTRS)
1985-01-01
The Institute for Computer Applications in Science and Engineering computer science program is discussed in outline form. Information is given on such topics as problem decomposition, algorithm development, programming languages, and parallel architectures.
Rebooting Computers as Learning Machines
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeBenedictis, Erik P.
Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.
Image Understanding Architecture
1991-09-01
architecture to support real-time, knowledge -based image understanding , and develop the software support environment that will be needed to utilize...NUMBER OF PAGES Image Understanding Architecture, Knowledge -Based Vision, AI Real-Time Computer Vision, Software Simulator, Parallel Processor IL PRICE... information . In addition to sensory and knowledge -based processing it is useful to introduce a level of symbolic processing. Thus, vision researchers
NASA Technical Reports Server (NTRS)
Rutishauser, David
2006-01-01
The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.
The 2nd Symposium on the Frontiers of Massively Parallel Computations
NASA Technical Reports Server (NTRS)
Mills, Ronnie (Editor)
1988-01-01
Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.
Doing It Right: 366 answers to computing questions you didn't know you had
DOE Office of Scientific and Technical Information (OSTI.GOV)
Herring, Stuart Davis
Slides include information on history: version control, version control: branches, version control: Git, releases, requirements, readability, readability control flow, global variables, architecture, architecture redundancy, processes, input/output, unix, etcetera.
OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems.
Stone, John E; Gohara, David; Shi, Guochun
2010-05-01
We provide an overview of the key architectural features of recent microprocessor designs and describe the programming model and abstractions provided by OpenCL, a new parallel programming standard targeting these architectures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Yao; Balaprakash, Prasanna; Meng, Jiayuan
We present Raexplore, a performance modeling framework for architecture exploration. Raexplore enables rapid, automated, and systematic search of architecture design space by combining hardware counter-based performance characterization and analytical performance modeling. We demonstrate Raexplore for two recent manycore processors IBM Blue- Gene/Q compute chip and Intel Xeon Phi, targeting a set of scientific applications. Our framework is able to capture complex interactions between architectural components including instruction pipeline, cache, and memory, and to achieve a 3–22% error for same-architecture and cross-architecture performance predictions. Furthermore, we apply our framework to assess the two processors, and discover and evaluate a list ofmore » architectural scaling options for future processor designs.« less
NASA Workshop on Computational Structural Mechanics 1987, part 1
NASA Technical Reports Server (NTRS)
Sykes, Nancy P. (Editor)
1989-01-01
Topics in Computational Structural Mechanics (CSM) are reviewed. CSM parallel structural methods, a transputer finite element solver, architectures for multiprocessor computers, and parallel eigenvalue extraction are among the topics discussed.
Engineering and Computing Portal to Solve Environmental Problems
NASA Astrophysics Data System (ADS)
Gudov, A. M.; Zavozkin, S. Y.; Sotnikov, I. Y.
2018-01-01
This paper describes architecture and services of the Engineering and Computing Portal, which is considered to be a complex solution that provides access to high-performance computing resources, enables to carry out computational experiments, teach parallel technologies and solve computing tasks, including technogenic safety ones.
Recent Trends in Spintronics-Based Nanomagnetic Logic
NASA Astrophysics Data System (ADS)
Das, Jayita; Alam, Syed M.; Bhanja, Sanjukta
2014-09-01
With the growing concerns of standby power in sub-100-nm CMOS technologies, alternative computing techniques and memory technologies are explored. Spin transfer torque magnetoresistive RAM (STT-MRAM) is one such nonvolatile memory relying on magnetic tunnel junctions (MTJs) to store information. It uses spin transfer torque to write information and magnetoresistance to read information. In 2012, Everspin Technologies, Inc. commercialized the first 64Mbit Spin Torque MRAM. On the computing end, nanomagnetic logic (NML) is a promising technique with zero leakage and high data retention. In 2000, Cowburn and Welland first demonstrated its potential in logic and information propagation through magnetostatic interaction in a chain of single domain circular nanomagnetic dots of Supermalloy (Ni80Fe14Mo5X1, X is other metals). In 2006, Imre et al. demonstrated wires and majority gates followed by coplanar cross wire systems demonstration in 2010 by Pulecio et al. Since 2004 researchers have also investigated the potential of MTJs in logic. More recently with dipolar coupling between MTJs demonstrated in 2012, logic-in-memory architecture with STT-MRAM have been investigated. The architecture borrows the computing concept from NML and read and write style from MRAM. The architecture can switch its operation between logic and memory modes with clock as classifier. Further through logic partitioning between MTJ and CMOS plane, a significant performance boost has been observed in basic computing blocks within the architecture. In this work, we have explored the developments in NML, in MTJs and more recent developments in hybrid MTJ/CMOS logic-in-memory architecture and its unique logic partitioning capability.
Handsfield, Geoffrey G; Bolsterlee, Bart; Inouye, Joshua M; Herbert, Robert D; Besier, Thor F; Fernandez, Justin W
2017-12-01
Determination of skeletal muscle architecture is important for accurately modeling muscle behavior. Current methods for 3D muscle architecture determination can be costly and time-consuming, making them prohibitive for clinical or modeling applications. Computational approaches such as Laplacian flow simulations can estimate muscle fascicle orientation based on muscle shape and aponeurosis location. The accuracy of this approach is unknown, however, since it has not been validated against other standards for muscle architecture determination. In this study, muscle architectures from the Laplacian approach were compared to those determined from diffusion tensor imaging in eight adult medial gastrocnemius muscles. The datasets were subdivided into training and validation sets, and computational fluid dynamics software was used to conduct Laplacian simulations. In training sets, inputs of muscle geometry, aponeurosis location, and geometric flow guides resulted in good agreement between methods. Application of the method to validation sets showed no significant differences in pennation angle (mean difference [Formula: see text] or fascicle length (mean difference 0.9 mm). Laplacian simulation was thus effective at predicting gastrocnemius muscle architectures in healthy volunteers using imaging-derived muscle shape and aponeurosis locations. This method may serve as a tool for determining muscle architecture in silico and as a complement to other approaches.
Fast semivariogram computation using FPGA architectures
NASA Astrophysics Data System (ADS)
Lagadapati, Yamuna; Shirvaikar, Mukul; Dong, Xuanliang
2015-02-01
The semivariogram is a statistical measure of the spatial distribution of data and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. The semivariogram is a plot of semivariances for different lag distances between pixels. A semi-variance, γ(h), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h. Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O(n2). Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz, but they can perform tens of thousands of calculations per clock cycle while operating in the low range of power. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. The design consists of several modules dedicated to the constituent computational tasks. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. Anisotropic semivariogram implementation is anticipated to be an extension of the current architecture, ostensibly based on refinements to the current modules. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from MRI scans are utilized for the experiments. Computational speedup is measured with respect to Matlab implementation on a personal computer with an Intel i7 multi-core processor. Preliminary simulation results indicate that a significant advantage in speed can be attained by the architectures, making the algorithm viable for implementation in medical devices
Kou, W; Pandolfino, J E; Kahrilas, P J; Patankar, N A
2017-06-01
Based on a fully coupled computational model of esophageal transport, we analyzed how varied esophageal muscle fiber architecture and/or dual contraction waves (CWs) affect bolus transport. Specifically, we studied the luminal pressure profile in those cases to better understand possible origins of the peristaltic transition zone. Two groups of studies were conducted using a computational model. The first studied esophageal transport with circumferential-longitudinal fiber architecture, helical fiber architecture and various combinations of the two. In the second group, cases with dual CWs and varied muscle fiber architecture were simulated. Overall transport characteristics were examined and the space-time profiles of luminal pressure were plotted and compared. Helical muscle fiber architecture featured reduced circumferential wall stress, greater esophageal distensibility, and greater axial shortening. Non-uniform fiber architecture featured a peristaltic pressure trough between two high-pressure segments. The distal pressure segment showed greater amplitude than the proximal segment, consistent with experimental data. Dual CWs also featured a pressure trough between two high-pressure segments. However, the minimum pressure in the region of overlap was much lower, and the amplitudes of the two high-pressure segments were similar. The efficacy of esophageal transport is greatly affected by muscle fiber architecture. The peristaltic transition zone may be attributable to non-uniform architecture of muscle fibers along the length of the esophagus and/or dual CWs. The difference in amplitude between the proximal and distal pressure segments may be attributable to non-uniform muscle fiber architecture. © 2017 John Wiley & Sons Ltd.
Analysis of Defenses Against Code Reuse Attacks on Modern and New Architectures
2015-09-01
soundness or completeness. An incomplete analysis will produce extra edges in the CFG that might allow an attacker to slip through. An unsound analysis...Analysis of Defenses Against Code Reuse Attacks on Modern and New Architectures by Isaac Noah Evans Submitted to the Department of Electrical...Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Engineering in Electrical Engineering and Computer
Patterns and Practices for Future Architectures
2014-08-01
14. SUBJECT TERMS computing architecture, graph algorithms, high-performance computing, big data , GPU 15. NUMBER OF PAGES 44 16. PRICE CODE 17...at Vertex 1 6 Figure 4: Data Structures Created by Kernel 1 of Single CPU, List Implementation Using the Graph in the Example from Section 1.2 9...Figure 5: Kernel 2 of Graph500 BFS Reference Implementation: Single CPU, List 10 Figure 6: Data Structures for Sequential CSR Algorithm 12 Figure 7
NASA Astrophysics Data System (ADS)
Yang, Wei; Hall, Trevor J.
2013-12-01
The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.
Information Architecture for Quality Management Support in Hospitals.
Rocha, Álvaro; Freixo, Jorge
2015-10-01
Quality Management occupies a strategic role in organizations, and the adoption of computer tools within an aligned information architecture facilitates the challenge of making more with less, promoting the development of a competitive edge and sustainability. A formal Information Architecture (IA) lends organizations an enhanced knowledge but, above all, favours management. This simplifies the reinvention of processes, the reformulation of procedures, bridging and the cooperation amongst the multiple actors of an organization. In the present investigation work we planned the IA for the Quality Management System (QMS) of a Hospital, which allowed us to develop and implement the QUALITUS (QUALITUS, name of the computer application developed to support Quality Management in a Hospital Unit) computer application. This solution translated itself in significant gains for the Hospital Unit under study, accelerating the quality management process and reducing the tasks, the number of documents, the information to be filled in and information errors, amongst others.
A Cloud-Based Simulation Architecture for Pandemic Influenza Simulation
Eriksson, Henrik; Raciti, Massimiliano; Basile, Maurizio; Cunsolo, Alessandro; Fröberg, Anders; Leifler, Ola; Ekberg, Joakim; Timpka, Toomas
2011-01-01
High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface. PMID:22195089
The MasPar MP-1 As a Computer Arithmetic Laboratory
Anuta, Michael A.; Lozier, Daniel W.; Turner, Peter R.
1996-01-01
This paper is a blueprint for the use of a massively parallel SIMD computer architecture for the simulation of various forms of computer arithmetic. The particular system used is a DEC/MasPar MP-1 with 4096 processors in a square array. This architecture has many advantages for such simulations due largely to the simplicity of the individual processors. Arithmetic operations can be spread across the processor array to simulate a hardware chip. Alternatively they may be performed on individual processors to allow simulation of a massively parallel implementation of the arithmetic. Compromises between these extremes permit speed-area tradeoffs to be examined. The paper includes a description of the architecture and its features. It then summarizes some of the arithmetic systems which have been, or are to be, implemented. The implementation of the level-index and symmetric level-index, LI and SLI, systems is described in some detail. An extensive bibliography is included. PMID:27805123
PEM-PCA: a parallel expectation-maximization PCA face recognition architecture.
Rujirakul, Kanokmon; So-In, Chakchai; Arnonkijpanich, Banchar
2014-01-01
Principal component analysis or PCA has been traditionally used as one of the feature extraction techniques in face recognition systems yielding high accuracy when requiring a small number of features. However, the covariance matrix and eigenvalue decomposition stages cause high computational complexity, especially for a large database. Thus, this research presents an alternative approach utilizing an Expectation-Maximization algorithm to reduce the determinant matrix manipulation resulting in the reduction of the stages' complexity. To improve the computational time, a novel parallel architecture was employed to utilize the benefits of parallelization of matrix computation during feature extraction and classification stages including parallel preprocessing, and their combinations, so-called a Parallel Expectation-Maximization PCA architecture. Comparing to a traditional PCA and its derivatives, the results indicate lower complexity with an insignificant difference in recognition precision leading to high speed face recognition systems, that is, the speed-up over nine and three times over PCA and Parallel PCA.
Evolutionary Telemetry and Command Processor (TCP) architecture
NASA Technical Reports Server (NTRS)
Schneider, John R.
1992-01-01
A low cost, modular, high performance, and compact Telemetry and Command Processor (TCP) is being built as the foundation of command and data handling subsystems for the next generation of satellites. The TCP product line will support command and telemetry requirements for small to large spacecraft and from low to high rate data transmission. It is compatible with the latest TDRSS, STDN and SGLS transponders and provides CCSDS protocol communications in addition to standard TDM formats. Its high performance computer provides computing resources for hosted flight software. Layered and modular software provides common services using standardized interfaces to applications thereby enhancing software re-use, transportability, and interoperability. The TCP architecture is based on existing standards, distributed networking, distributed and open system computing, and packet technology. The first TCP application is planned for the 94 SDIO SPAS 3 mission. The architecture enhances rapid tailoring of functions thereby reducing costs and schedules developed for individual spacecraft missions.
Implementation of an ADI method on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1987-01-01
The implementation of an ADI method for solving the diffusion equation on three parallel/vector computers is discussed. The computers were chosen so as to encompass a variety of architectures. They are: the MPP, an SIMD machine with 16K bit serial processors; FLEX/32, an MIMD machine with 20 processors; and CRAY/2, an MIMD machine with four vector processors. The Gaussian elimination algorithm is used to solve a set of tridiagonal systems on the FLEX/32 and CRAY/2 while the cyclic elimination algorithm is used to solve these systems on the MPP. The implementation of the method is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.
Implementation of an ADI method on parallel computers
NASA Technical Reports Server (NTRS)
Fatoohi, Raad A.; Grosch, Chester E.
1987-01-01
In this paper the implementation of an ADI method for solving the diffusion equation on three parallel/vector computers is discussed. The computers were chosen so as to encompass a variety of architectures. They are the MPP, an SIMD machine with 16-Kbit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2, an MIMD machine with four vector processors. The Gaussian elimination algorithm is used to solve a set of tridiagonal systems on the Flex/32 and Cray/2 while the cyclic elimination algorithm is used to solve these systems on the MPP. The implementation of the method is discussed in relation to these architectures and measures of the performance on each machine are given. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally conclusions are presented.
Essential issues in multiprocessor systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gajski, D.D.; Peir, J.K.
1985-06-01
During the past several years, a great number of proposals have been made with the objective to increase supercomputer performance by an order of magnitude on the basis of a utilization of new computer architectures. The present paper is concerned with a suitable classification scheme for comparing these architectures. It is pointed out that there are basically four schools of thought as to the most important factor for an enhancement of computer performance. According to one school, the development of faster circuits will make it possible to retain present architectures, except, possibly, for a mechanism providing synchronization of parallel processes.more » A second school assigns priority to the optimization and vectorization of compilers, which will detect parallelism and help users to write better parallel programs. A third school believes in the predominant importance of new parallel algorithms, while the fourth school supports new models of computation. The merits of the four approaches are critically evaluated. 50 references.« less
Computers for symbolic processing
NASA Technical Reports Server (NTRS)
Wah, Benjamin W.; Lowrie, Matthew B.; Li, Guo-Jie
1989-01-01
A detailed survey on the motivations, design, applications, current status, and limitations of computers designed for symbolic processing is provided. Symbolic processing computations are performed at the word, relation, or meaning levels, and the knowledge used in symbolic applications may be fuzzy, uncertain, indeterminate, and ill represented. Various techniques for knowledge representation and processing are discussed from both the designers' and users' points of view. The design and choice of a suitable language for symbolic processing and the mapping of applications into a software architecture are then considered. The process of refining the application requirements into hardware and software architectures is treated, and state-of-the-art sequential and parallel computers designed for symbolic processing are discussed.
Flynn, Allen J; Boisvert, Peter; Gittlen, Nate; Gross, Colin; Iott, Brad; Lagoze, Carl; Meng, George; Friedman, Charles P
2018-01-01
The Knowledge Grid (KGrid) is a research and development program toward infrastructure capable of greatly decreasing latency between the publication of new biomedical knowledge and its widespread uptake into practice. KGrid comprises digital knowledge objects, an online Library to store them, and an Activator that uses them to provide Knowledge-as-a-Service (KaaS). KGrid's Activator enables computable biomedical knowledge, held in knowledge objects, to be rapidly deployed at Internet-scale in cloud computing environments for improved health. Here we present the Activator, its system architecture and primary functions.
A visual programming environment for the Navier-Stokes computer
NASA Technical Reports Server (NTRS)
Tomboulian, Sherryl; Crockett, Thomas W.; Middleton, David
1988-01-01
The Navier-Stokes computer is a high-performance, reconfigurable, pipelined machine designed to solve large computational fluid dynamics problems. Due to the complexity of the architecture, development of effective, high-level language compilers for the system appears to be a very difficult task. Consequently, a visual programming methodology has been developed which allows users to program the system at an architectural level by constructing diagrams of the pipeline configuration. These schematic program representations can then be checked for validity and automatically translated into machine code. The visual environment is illustrated by using a prototype graphical editor to program an example problem.
Improving Quantum Gate Simulation using a GPU
NASA Astrophysics Data System (ADS)
Gutierrez, Eladio; Romero, Sergio; Trenas, Maria A.; Zapata, Emilio L.
2008-11-01
Due to the increasing computing power of the graphics processing units (GPU), they are becoming more and more popular when solving general purpose algorithms. As the simulation of quantum computers results on a problem with exponential complexity, it is advisable to perform a parallel computation, such as the one provided by the SIMD multiprocessors present in recent GPUs. In this paper, we focus on an important quantum algorithm, the quantum Fourier transform (QTF), in order to evaluate different parallelization strategies on a novel GPU architecture. Our implementation makes use of the new CUDA software/hardware architecture developed recently by NVIDIA.
A resource management architecture based on complex network theory in cloud computing federation
NASA Astrophysics Data System (ADS)
Zhang, Zehua; Zhang, Xuejie
2011-10-01
Cloud Computing Federation is a main trend of Cloud Computing. Resource Management has significant effect on the design, realization, and efficiency of Cloud Computing Federation. Cloud Computing Federation has the typical characteristic of the Complex System, therefore, we propose a resource management architecture based on complex network theory for Cloud Computing Federation (abbreviated as RMABC) in this paper, with the detailed design of the resource discovery and resource announcement mechanisms. Compare with the existing resource management mechanisms in distributed computing systems, a Task Manager in RMABC can use the historical information and current state data get from other Task Managers for the evolution of the complex network which is composed of Task Managers, thus has the advantages in resource discovery speed, fault tolerance and adaptive ability. The result of the model experiment confirmed the advantage of RMABC in resource discovery performance.
Parallel Signal Processing and System Simulation using aCe
NASA Technical Reports Server (NTRS)
Dorband, John E.; Aburdene, Maurice F.
2003-01-01
Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).
Parallel language constructs for tensor product computations on loosely coupled architectures
NASA Technical Reports Server (NTRS)
Mehrotra, Piyush; Vanrosendale, John
1989-01-01
Distributed memory architectures offer high levels of performance and flexibility, but have proven awkard to program. Current languages for nonshared memory architectures provide a relatively low level programming environment, and are poorly suited to modular programming, and to the construction of libraries. A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. Tensor product array computations are focused on along with a simple but important class of numerical algorithms. The problem of programming 1-D kernal routines is focused on first, such as parallel tridiagonal solvers, and then how such parallel kernels can be combined to form parallel tensor product algorithms is examined.
NASA Technical Reports Server (NTRS)
Smith, T. B., III; Lala, J. H.
1984-01-01
The FTMP architecture is a high reliability computer concept modeled after a homogeneous multiprocessor architecture. Elements of the FTMP are operated in tight synchronism with one another and hardware fault-detection and fault-masking is provided which is transparent to the software. Operating system design and user software design is thus greatly simplified. Performance of the FTMP is also comparable to that of a simplex equivalent due to the efficiency of fault handling hardware. The FTMP project constructed an engineering module of the FTMP, programmed the machine and extensively tested the architecture through fault injection and other stress testing. This testing confirmed the soundness of the FTMP concepts.
A highly efficient 3D level-set grain growth algorithm tailored for ccNUMA architecture
NASA Astrophysics Data System (ADS)
Mießen, C.; Velinov, N.; Gottstein, G.; Barrales-Mora, L. A.
2017-12-01
A highly efficient simulation model for 2D and 3D grain growth was developed based on the level-set method. The model introduces modern computational concepts to achieve excellent performance on parallel computer architectures. Strong scalability was measured on cache-coherent non-uniform memory access (ccNUMA) architectures. To achieve this, the proposed approach considers the application of local level-set functions at the grain level. Ideal and non-ideal grain growth was simulated in 3D with the objective to study the evolution of statistical representative volume elements in polycrystals. In addition, microstructure evolution in an anisotropic magnetic material affected by an external magnetic field was simulated.
ERIC Educational Resources Information Center
Stocco, Andrea
2018-01-01
Several attempts have been made previously to provide a biological grounding for cognitive architectures by relating their components to the computations of specific brain circuits. Often, the architecture's action selection system is identified with the basal ganglia. However, this identification overlooks one of the most important features of…
Parallel Architectures for Planetary Exploration Requirements (PAPER)
NASA Technical Reports Server (NTRS)
Cezzar, Ruknet; Sen, Ranjan K.
1989-01-01
The Parallel Architectures for Planetary Exploration Requirements (PAPER) project is essentially research oriented towards technology insertion issues for NASA's unmanned planetary probes. It was initiated to complement and augment the long-term efforts for space exploration with particular reference to NASA/LaRC's (NASA Langley Research Center) research needs for planetary exploration missions of the mid and late 1990s. The requirements for space missions as given in the somewhat dated Advanced Information Processing Systems (AIPS) requirements document are contrasted with the new requirements from JPL/Caltech involving sensor data capture and scene analysis. It is shown that more stringent requirements have arisen as a result of technological advancements. Two possible architectures, the AIPS Proof of Concept (POC) configuration and the MAX Fault-tolerant dataflow multiprocessor, were evaluated. The main observation was that the AIPS design is biased towards fault tolerance and may not be an ideal architecture for planetary and deep space probes due to high cost and complexity. The MAX concepts appears to be a promising candidate, except that more detailed information is required. The feasibility for adding neural computation capability to this architecture needs to be studied. Key impact issues for architectural design of computing systems meant for planetary missions were also identified.
OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems
Stone, John E.; Gohara, David; Shi, Guochun
2010-01-01
We provide an overview of the key architectural features of recent microprocessor designs and describe the programming model and abstractions provided by OpenCL, a new parallel programming standard targeting these architectures. PMID:21037981
An Integrative Architecture for a Sensor-Supported Trust Management System
Trček, Denis
2012-01-01
Trust plays a key role not only in e-worlds and emerging pervasive computing environments, but also already for millennia in human societies. Trust management solutions that have being around now for some fifteen years were primarily developed for the above mentioned cyber environments and they are typically focused on artificial agents, sensors, etc. However, this paper presents extensions of a new methodology together with architecture for trust management support that is focused on humans and human-like agents. With this methodology and architecture sensors play a crucial role. The architecture presents an already deployable tool for multi and interdisciplinary research in various areas where humans are involved. It provides new ways to obtain an insight into dynamics and evolution of such structures, not only in pervasive computing environments, but also in other important areas like management and decision making support. PMID:23112628
Developing Information Power Grid Based Algorithms and Software
NASA Technical Reports Server (NTRS)
Dongarra, Jack
1998-01-01
This exploratory study initiated our effort to understand performance modeling on parallel systems. The basic goal of performance modeling is to understand and predict the performance of a computer program or set of programs on a computer system. Performance modeling has numerous applications, including evaluation of algorithms, optimization of code implementations, parallel library development, comparison of system architectures, parallel system design, and procurement of new systems. Our work lays the basis for the construction of parallel libraries that allow for the reconstruction of application codes on several distinct architectures so as to assure performance portability. Following our strategy, once the requirements of applications are well understood, one can then construct a library in a layered fashion. The top level of this library will consist of architecture-independent geometric, numerical, and symbolic algorithms that are needed by the sample of applications. These routines should be written in a language that is portable across the targeted architectures.
NASA Technical Reports Server (NTRS)
Jacklin, S. A.; Leyland, J. A.; Warmbrodt, W.
1985-01-01
Modern control systems must typically perform real-time identification and control, as well as coordinate a host of other activities related to user interaction, online graphics, and file management. This paper discusses five global design considerations which are useful to integrate array processor, multimicroprocessor, and host computer system architectures into versatile, high-speed controllers. Such controllers are capable of very high control throughput, and can maintain constant interaction with the nonreal-time or user environment. As an application example, the architecture of a high-speed, closed-loop controller used to actively control helicopter vibration is briefly discussed. Although this system has been designed for use as the controller for real-time rotorcraft dynamics and control studies in a wind tunnel environment, the controller architecture can generally be applied to a wide range of automatic control applications.
NASA Astrophysics Data System (ADS)
Xiao, Jian; Zhang, Mingqiang; Tian, Haiping; Huang, Bo; Fu, Wenlong
2018-02-01
In this paper, a novel prognostics and health management system architecture for hydropower plant equipment was proposed based on fog computing and Docker container. We employed the fog node to improve the real-time processing ability of improving the cloud architecture-based prognostics and health management system and overcome the problems of long delay time, network congestion and so on. Then Storm-based stream processing of fog node was present and could calculate the health index in the edge of network. Moreover, the distributed micros-service and Docker container architecture of hydropower plants equipment prognostics and health management was also proposed. Using the micro service architecture proposed in this paper, the hydropower unit can achieve the goal of the business intercommunication and seamless integration of different equipment and different manufacturers. Finally a real application case is given in this paper.
CUDA Optimization Strategies for Compute- and Memory-Bound Neuroimaging Algorithms
Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W.
2011-01-01
As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. PMID:21159404
CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.
Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W
2012-06-01
As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Stamatakis, Alexandros; Ott, Michael
2008-12-27
The continuous accumulation of sequence data, for example, due to novel wet-laboratory techniques such as pyrosequencing, coupled with the increasing popularity of multi-gene phylogenies and emerging multi-core processor architectures that face problems of cache congestion, poses new challenges with respect to the efficient computation of the phylogenetic maximum-likelihood (ML) function. Here, we propose two approaches that can significantly speed up likelihood computations that typically represent over 95 per cent of the computational effort conducted by current ML or Bayesian inference programs. Initially, we present a method and an appropriate data structure to efficiently compute the likelihood score on 'gappy' multi-gene alignments. By 'gappy' we denote sampling-induced gaps owing to missing sequences in individual genes (partitions), i.e. not real alignment gaps. A first proof-of-concept implementation in RAXML indicates that this approach can accelerate inferences on large and gappy alignments by approximately one order of magnitude. Moreover, we present insights and initial performance results on multi-core architectures obtained during the transition from an OpenMP-based to a Pthreads-based fine-grained parallelization of the ML function.
NASA Astrophysics Data System (ADS)
Elkurdi, Yousef; Fernández, David; Souleimanov, Evgueni; Giannacopoulos, Dennis; Gross, Warren J.
2008-04-01
The Finite Element Method (FEM) is a computationally intensive scientific and engineering analysis tool that has diverse applications ranging from structural engineering to electromagnetic simulation. The trends in floating-point performance are moving in favor of Field-Programmable Gate Arrays (FPGAs), hence increasing interest has grown in the scientific community to exploit this technology. We present an architecture and implementation of an FPGA-based sparse matrix-vector multiplier (SMVM) for use in the iterative solution of large, sparse systems of equations arising from FEM applications. FEM matrices display specific sparsity patterns that can be exploited to improve the efficiency of hardware designs. Our architecture exploits FEM matrix sparsity structure to achieve a balance between performance and hardware resource requirements by relying on external SDRAM for data storage while utilizing the FPGAs computational resources in a stream-through systolic approach. The architecture is based on a pipelined linear array of processing elements (PEs) coupled with a hardware-oriented matrix striping algorithm and a partitioning scheme which enables it to process arbitrarily big matrices without changing the number of PEs in the architecture. Therefore, this architecture is only limited by the amount of external RAM available to the FPGA. The implemented SMVM-pipeline prototype contains 8 PEs and is clocked at 110 MHz obtaining a peak performance of 1.76 GFLOPS. For 8 GB/s of memory bandwidth typical of recent FPGA systems, this architecture can achieve 1.5 GFLOPS sustained performance. Using multiple instances of the pipeline, linear scaling of the peak and sustained performance can be achieved. Our stream-through architecture provides the added advantage of enabling an iterative implementation of the SMVM computation required by iterative solution techniques such as the conjugate gradient method, avoiding initialization time due to data loading and setup inside the FPGA internal memory.
Methodology of modeling and measuring computer architectures for plasma simulations
NASA Technical Reports Server (NTRS)
Wang, L. P. T.
1977-01-01
A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.
Architectural Aspects of Grid Computing and its Global Prospects for E-Science Community
NASA Astrophysics Data System (ADS)
Ahmad, Mushtaq
2008-05-01
The paper reviews the imminent Architectural Aspects of Grid Computing for e-Science community for scientific research and business/commercial collaboration beyond physical boundaries. Grid Computing provides all the needed facilities; hardware, software, communication interfaces, high speed internet, safe authentication and secure environment for collaboration of research projects around the globe. It provides highly fast compute engine for those scientific and engineering research projects and business/commercial applications which are heavily compute intensive and/or require humongous amounts of data. It also makes possible the use of very advanced methodologies, simulation models, expert systems and treasure of knowledge available around the globe under the umbrella of knowledge sharing. Thus it makes possible one of the dreams of global village for the benefit of e-Science community across the globe.
1983-12-30
AD-Ri46 57? ARCHITECTURE DESIGN AND SYSTEM; PERFORMANCE ASSESSMENT i/i AND DEVELOPMENT ME..(U) NAVAL SURFACE WEAPONS CENTER SILYER SPRING MD J...AD-A 146 577 NSIWC TR 83-324 ARCHITECTURE , DESIGN , AND SYSTEM; PERFORMANCE ASSESSMENT AND DEVELOPMENT METHODOLOGY...REPORT NUMBER 12. GOVT ACCESSION NO.3. RECIPIENT’S CATALOG NUMBER NSWC TR 83-324 10- 1 1 51’ 4. ?ITLE (and subtitle) ARCHITECTURE , DESIGN , AND SYSTEM; S
MPI implementation of PHOENICS: A general purpose computational fluid dynamics code
NASA Astrophysics Data System (ADS)
Simunovic, S.; Zacharia, T.; Baltas, N.; Spalding, D. B.
1995-03-01
PHOENICS is a suite of computational analysis programs that are used for simulation of fluid flow, heat transfer, and dynamical reaction processes. The parallel version of the solver EARTH for the Computational Fluid Dynamics (CFD) program PHOENICS has been implemented using Message Passing Interface (MPI) standard. Implementation of MPI version of PHOENICS makes this computational tool portable to a wide range of parallel machines and enables the use of high performance computing for large scale computational simulations. MPI libraries are available on several parallel architectures making the program usable across different architectures as well as on heterogeneous computer networks. The Intel Paragon NX and MPI versions of the program have been developed and tested on massively parallel supercomputers Intel Paragon XP/S 5, XP/S 35, and Kendall Square Research, and on the multiprocessor SGI Onyx computer at Oak Ridge National Laboratory. The preliminary testing results of the developed program have shown scalable performance for reasonably sized computational domains.
MPI implementation of PHOENICS: A general purpose computational fluid dynamics code
DOE Office of Scientific and Technical Information (OSTI.GOV)
Simunovic, S.; Zacharia, T.; Baltas, N.
1995-04-01
PHOENICS is a suite of computational analysis programs that are used for simulation of fluid flow, heat transfer, and dynamical reaction processes. The parallel version of the solver EARTH for the Computational Fluid Dynamics (CFD) program PHOENICS has been implemented using Message Passing Interface (MPI) standard. Implementation of MPI version of PHOENICS makes this computational tool portable to a wide range of parallel machines and enables the use of high performance computing for large scale computational simulations. MPI libraries are available on several parallel architectures making the program usable across different architectures as well as on heterogeneous computer networks. Themore » Intel Paragon NX and MPI versions of the program have been developed and tested on massively parallel supercomputers Intel Paragon XP/S 5, XP/S 35, and Kendall Square Research, and on the multiprocessor SGI Onyx computer at Oak Ridge National Laboratory. The preliminary testing results of the developed program have shown scalable performance for reasonably sized computational domains.« less
Chen, Qingkui; Zhao, Deyu; Wang, Jingjuan
2017-01-01
This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services. PMID:28777325
Fang, Yuling; Chen, Qingkui; Xiong, Neal N; Zhao, Deyu; Wang, Jingjuan
2017-08-04
This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes' diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.
Traffic Simulations on Parallel Computers Using Domain Decomposition Techniques
DOT National Transportation Integrated Search
1995-01-01
Large scale simulations of Intelligent Transportation Systems (ITS) can only be acheived by using the computing resources offered by parallel computing architectures. Domain decomposition techniques are proposed which allow the performance of traffic...
Computing Project, Marc develops high-fidelity turbulence models to enhance simulation accuracy and efficient numerical algorithms for future high performance computing hardware architectures. Research Interests High performance computing High order numerical methods for computational fluid dynamics Fluid
CPU SIM: A Computer Simulator for Use in an Introductory Computer Organization-Architecture Class.
ERIC Educational Resources Information Center
Skrein, Dale
1994-01-01
CPU SIM, an interactive low-level computer simulation package that runs on the Macintosh computer, is described. The program is designed for instructional use in the first or second year of undergraduate computer science, to teach various features of typical computer organization through hands-on exercises. (MSE)
ERIC Educational Resources Information Center
Conn, Samuel S.; Reichgelt, Han
2013-01-01
Cloud computing represents an architecture and paradigm of computing designed to deliver infrastructure, platforms, and software as constructible computing resources on demand to networked users. As campuses are challenged to better accommodate academic needs for applications and computing environments, cloud computing can provide an accommodating…
Cladé, Thierry; Snyder, Joshua C.
2010-01-01
Clinical trials which use imaging typically require data management and workflow integration across several parties. We identify opportunities for all parties involved to realize benefits with a modular interoperability model based on service-oriented architecture and grid computing principles. We discuss middleware products for implementation of this model, and propose caGrid as an ideal candidate due to its healthcare focus; free, open source license; and mature developer tools and support. PMID:20449775
Algorithms and software for solving finite element equations on serial and parallel architectures
NASA Technical Reports Server (NTRS)
George, Alan
1989-01-01
Over the past 15 years numerous new techniques have been developed for solving systems of equations and eigenvalue problems arising in finite element computations. A package called SPARSPAK has been developed by the author and his co-workers which exploits these new methods. The broad objective of this research project is to incorporate some of this software in the Computational Structural Mechanics (CSM) testbed, and to extend the techniques for use on multiprocessor architectures.
Design of a real-time wind turbine simulator using a custom parallel architecture
NASA Technical Reports Server (NTRS)
Hoffman, John A.; Gluck, R.; Sridhar, S.
1995-01-01
The design of a new parallel-processing digital simulator is described. The new simulator has been developed specifically for analysis of wind energy systems in real time. The new processor has been named: the Wind Energy System Time-domain simulator, version 3 (WEST-3). Like previous WEST versions, WEST-3 performs many computations in parallel. The modules in WEST-3 are pure digital processors, however. These digital processors can be programmed individually and operated in concert to achieve real-time simulation of wind turbine systems. Because of this programmability, WEST-3 is very much more flexible and general than its two predecessors. The design features of WEST-3 are described to show how the system produces high-speed solutions of nonlinear time-domain equations. WEST-3 has two very fast Computational Units (CU's) that use minicomputer technology plus special architectural features that make them many times faster than a microcomputer. These CU's are needed to perform the complex computations associated with the wind turbine rotor system in real time. The parallel architecture of the CU causes several tasks to be done in each cycle, including an IO operation and the combination of a multiply, add, and store. The WEST-3 simulator can be expanded at any time for additional computational power. This is possible because the CU's interfaced to each other and to other portions of the simulation using special serial buses. These buses can be 'patched' together in essentially any configuration (in a manner very similar to the programming methods used in analog computation) to balance the input/ output requirements. CU's can be added in any number to share a given computational load. This flexible bus feature is very different from many other parallel processors which usually have a throughput limit because of rigid bus architecture.
Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N
2006-12-01
Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.
Craciun, Stefan; Brockmeier, Austin J; George, Alan D; Lam, Herman; Príncipe, José C
2011-01-01
Methods for decoding movements from neural spike counts using adaptive filters often rely on minimizing the mean-squared error. However, for non-Gaussian distribution of errors, this approach is not optimal for performance. Therefore, rather than using probabilistic modeling, we propose an alternate non-parametric approach. In order to extract more structure from the input signal (neuronal spike counts) we propose using minimum error entropy (MEE), an information-theoretic approach that minimizes the error entropy as part of an iterative cost function. However, the disadvantage of using MEE as the cost function for adaptive filters is the increase in computational complexity. In this paper we present a comparison between the decoding performance of the analytic Wiener filter and a linear filter trained with MEE, which is then mapped to a parallel architecture in reconfigurable hardware tailored to the computational needs of the MEE filter. We observe considerable speedup from the hardware design. The adaptation of filter weights for the multiple-input, multiple-output linear filters, necessary in motor decoding, is a highly parallelizable algorithm. It can be decomposed into many independent computational blocks with a parallel architecture readily mapped to a field-programmable gate array (FPGA) and scales to large numbers of neurons. By pipelining and parallelizing independent computations in the algorithm, the proposed parallel architecture has sublinear increases in execution time with respect to both window size and filter order.
DeepX: Deep Learning Accelerator for Restricted Boltzmann Machine Artificial Neural Networks.
Kim, Lok-Won
2018-05-01
Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs. The implemented RBM ANN accelerator (integrating network size, using 128 input cases per batch, and running at a 303-MHz clock frequency) integrated in a state-of-the art field-programmable gate array (FPGA) (Xilinx Virtex 7 XC7V-2000T) provides a computational performance of 301-billion connection-updates-per-second and about 193 times higher performance than a software solution running on general purpose processors. Most importantly, the architecture enables over 4 times (12 times in batch learning) higher performance compared with a previous work when both are implemented in an FPGA device (XC2VP70).
Efficient parallel implementation of active appearance model fitting algorithm on GPU.
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.
Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures. PMID:24723812
Rosen's (M,R) system as an X-machine.
Palmer, Michael L; Williams, Richard A; Gatherer, Derek
2016-11-07
Robert Rosen's (M,R) system is an abstract biological network architecture that is allegedly both irreducible to sub-models of its component states and non-computable on a Turing machine. (M,R) stands as an obstacle to both reductionist and mechanistic presentations of systems biology, principally due to its self-referential structure. If (M,R) has the properties claimed for it, computational systems biology will not be possible, or at best will be a science of approximate simulations rather than accurate models. Several attempts have been made, at both empirical and theoretical levels, to disprove this assertion by instantiating (M,R) in software architectures. So far, these efforts have been inconclusive. In this paper, we attempt to demonstrate why - by showing how both finite state machine and stream X-machine formal architectures fail to capture the self-referential requirements of (M,R). We then show that a solution may be found in communicating X-machines, which remove self-reference using parallel computation, and then synthesise such machine architectures with object-orientation to create a formal basis for future software instantiations of (M,R) systems. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Roadmap for caGrid, an Enterprise Grid Architecture for Biomedical Research
Saltz, Joel; Hastings, Shannon; Langella, Stephen; Oster, Scott; Kurc, Tahsin; Payne, Philip; Ferreira, Renato; Plale, Beth; Goble, Carole; Ervin, David; Sharma, Ashish; Pan, Tony; Permar, Justin; Brezany, Peter; Siebenlist, Frank; Madduri, Ravi; Foster, Ian; Shanbhag, Krishnakant; Mead, Charlie; Hong, Neil Chue
2012-01-01
caGrid is a middleware system which combines the Grid computing, the service oriented architecture, and the model driven architecture paradigms to support development of interoperable data and analytical resources and federation of such resources in a Grid environment. The functionality provided by caGrid is an essential and integral component of the cancer Biomedical Informatics Grid (caBIG™) program. This program is established by the National Cancer Institute as a nationwide effort to develop enabling informatics technologies for collaborative, multi-institutional biomedical research with the overarching goal of accelerating translational cancer research. Although the main application domain for caGrid is cancer research, the infrastructure provides a generic framework that can be employed in other biomedical research and healthcare domains. The development of caGrid is an ongoing effort, adding new functionality and improvements based on feedback and use cases from the community. This paper provides an overview of potential future architecture and tooling directions and areas of improvement for caGrid and caGrid-like systems. This summary is based on discussions at a roadmap workshop held in February with participants from biomedical research, Grid computing, and high performance computing communities. PMID:18560123
A roadmap for caGrid, an enterprise Grid architecture for biomedical research.
Saltz, Joel; Hastings, Shannon; Langella, Stephen; Oster, Scott; Kurc, Tahsin; Payne, Philip; Ferreira, Renato; Plale, Beth; Goble, Carole; Ervin, David; Sharma, Ashish; Pan, Tony; Permar, Justin; Brezany, Peter; Siebenlist, Frank; Madduri, Ravi; Foster, Ian; Shanbhag, Krishnakant; Mead, Charlie; Chue Hong, Neil
2008-01-01
caGrid is a middleware system which combines the Grid computing, the service oriented architecture, and the model driven architecture paradigms to support development of interoperable data and analytical resources and federation of such resources in a Grid environment. The functionality provided by caGrid is an essential and integral component of the cancer Biomedical Informatics Grid (caBIG) program. This program is established by the National Cancer Institute as a nationwide effort to develop enabling informatics technologies for collaborative, multi-institutional biomedical research with the overarching goal of accelerating translational cancer research. Although the main application domain for caGrid is cancer research, the infrastructure provides a generic framework that can be employed in other biomedical research and healthcare domains. The development of caGrid is an ongoing effort, adding new functionality and improvements based on feedback and use cases from the community. This paper provides an overview of potential future architecture and tooling directions and areas of improvement for caGrid and caGrid-like systems. This summary is based on discussions at a roadmap workshop held in February with participants from biomedical research, Grid computing, and high performance computing communities.
High Performance GPU-Based Fourier Volume Rendering.
Abdellah, Marwan; Eldeib, Ayman; Sharawi, Amr
2015-01-01
Fourier volume rendering (FVR) is a significant visualization technique that has been used widely in digital radiography. As a result of its (N (2)logN) time complexity, it provides a faster alternative to spatial domain volume rendering algorithms that are (N (3)) computationally complex. Relying on the Fourier projection-slice theorem, this technique operates on the spectral representation of a 3D volume instead of processing its spatial representation to generate attenuation-only projections that look like X-ray radiographs. Due to the rapid evolution of its underlying architecture, the graphics processing unit (GPU) became an attractive competent platform that can deliver giant computational raw power compared to the central processing unit (CPU) on a per-dollar-basis. The introduction of the compute unified device architecture (CUDA) technology enables embarrassingly-parallel algorithms to run efficiently on CUDA-capable GPU architectures. In this work, a high performance GPU-accelerated implementation of the FVR pipeline on CUDA-enabled GPUs is presented. This proposed implementation can achieve a speed-up of 117x compared to a single-threaded hybrid implementation that uses the CPU and GPU together by taking advantage of executing the rendering pipeline entirely on recent GPU architectures.
A brick-architecture-based mobile under-vehicle inspection system
NASA Astrophysics Data System (ADS)
Qian, Cheng; Page, David; Koschan, Andreas; Abidi, Mongi
2005-05-01
In this paper, a mobile scanning system for real-time under-vehicle inspection is presented, which is founded on a "Brick" architecture. In this "Brick" architecture, the inspection system is basically decomposed into bricks of three kinds: sensing, mobility, and computing. These bricks are physically and logically independent and communicate with each other by wireless communication. Each brick is mainly composed by five modules: data acquisition, data processing, data transmission, power, and self-management. These five modules can be further decomposed into submodules where the function and the interface are well-defined. Based on this architecture, the system is built by four bricks: two sensing bricks consisting of a range scanner and a line CCD, one mobility brick, and one computing brick. The sensing bricks capture geometric data and texture data of the under-vehicle scene, while the mobility brick provides positioning data along the motion path. Data of these three modalities are transmitted to the computing brick where they are fused and reconstruct a 3D under-vehicle model for visualization and danger inspection. This system has been successfully used in several military applications and proved to be an effective safer method for national security.
Real-time FPGA architectures for computer vision
NASA Astrophysics Data System (ADS)
Arias-Estrada, Miguel; Torres-Huitzil, Cesar
2000-03-01
This paper presents an architecture for real-time generic convolution of a mask and an image. The architecture is intended for fast low level image processing. The FPGA-based architecture takes advantage of the availability of registers in FPGAs to implement an efficient and compact module to process the convolutions. The architecture is designed to minimize the number of accesses to the image memory and is based on parallel modules with internal pipeline operation in order to improve its performance. The architecture is prototyped in a FPGA, but it can be implemented on a dedicated VLSI to reach higher clock frequencies. Complexity issues, FPGA resources utilization, FPGA limitations, and real time performance are discussed. Some results are presented and discussed.
Software Design for Real-Time Systems on Parallel Computers: Formal Specifications.
1996-04-01
This research investigated the important issues related to the analysis and design of real - time systems targeted to parallel architectures. In...particular, the software specification models for real - time systems on parallel architectures were evaluated. A survey of current formal methods for...uniprocessor real - time systems specifications was conducted to determine their extensibility in specifying real - time systems on parallel architectures. In
Programming model for distributed intelligent systems
NASA Technical Reports Server (NTRS)
Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.
1988-01-01
A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.
Simulation system architecture design for generic communications link
NASA Technical Reports Server (NTRS)
Tsang, Chit-Sang; Ratliff, Jim
1986-01-01
This paper addresses a computer simulation system architecture design for generic digital communications systems. It addresses the issues of an overall system architecture in order to achieve a user-friendly, efficient, and yet easily implementable simulation system. The system block diagram and its individual functional components are described in detail. Software implementation is discussed with the VAX/VMS operating system used as a target environment.
Computational Particle Dynamic Simulations on Multicore Processors (CPDMu) Final Report Phase I
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schmalz, Mark S
2011-07-24
Statement of Problem - Department of Energy has many legacy codes for simulation of computational particle dynamics and computational fluid dynamics applications that are designed to run on sequential processors and are not easily parallelized. Emerging high-performance computing architectures employ massively parallel multicore architectures (e.g., graphics processing units) to increase throughput. Parallelization of legacy simulation codes is a high priority, to achieve compatibility, efficiency, accuracy, and extensibility. General Statement of Solution - A legacy simulation application designed for implementation on mainly-sequential processors has been represented as a graph G. Mathematical transformations, applied to G, produce a graph representation {und G}more » for a high-performance architecture. Key computational and data movement kernels of the application were analyzed/optimized for parallel execution using the mapping G {yields} {und G}, which can be performed semi-automatically. This approach is widely applicable to many types of high-performance computing systems, such as graphics processing units or clusters comprised of nodes that contain one or more such units. Phase I Accomplishments - Phase I research decomposed/profiled computational particle dynamics simulation code for rocket fuel combustion into low and high computational cost regions (respectively, mainly sequential and mainly parallel kernels), with analysis of space and time complexity. Using the research team's expertise in algorithm-to-architecture mappings, the high-cost kernels were transformed, parallelized, and implemented on Nvidia Fermi GPUs. Measured speedups (GPU with respect to single-core CPU) were approximately 20-32X for realistic model parameters, without final optimization. Error analysis showed no loss of computational accuracy. Commercial Applications and Other Benefits - The proposed research will constitute a breakthrough in solution of problems related to efficient parallel computation of particle and fluid dynamics simulations. These problems occur throughout DOE, military and commercial sectors: the potential payoff is high. We plan to license or sell the solution to contractors for military and domestic applications such as disaster simulation (aerodynamic and hydrodynamic), Government agencies (hydrological and environmental simulations), and medical applications (e.g., in tomographic image reconstruction). Keywords - High-performance Computing, Graphic Processing Unit, Fluid/Particle Simulation. Summary for Members of Congress - Department of Energy has many simulation codes that must compute faster, to be effective. The Phase I research parallelized particle/fluid simulations for rocket combustion, for high-performance computing systems.« less
Proposed hardware architectures of particle filter for object tracking
NASA Astrophysics Data System (ADS)
Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED
2012-12-01
In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.
Performance analysis of parallel branch and bound search with the hypercube architecture
NASA Technical Reports Server (NTRS)
Mraz, Richard T.
1987-01-01
With the availability of commercial parallel computers, researchers are examining new classes of problems which might benefit from parallel computing. This paper presents results of an investigation of the class of search intensive problems. The specific problem discussed is the Least-Cost Branch and Bound search method of deadline job scheduling. The object-oriented design methodology was used to map the problem into a parallel solution. While the initial design was good for a prototype, the best performance resulted from fine-tuning the algorithm for a specific computer. The experiments analyze the computation time, the speed up over a VAX 11/785, and the load balance of the problem when using loosely coupled multiprocessor system based on the hypercube architecture.
Job Superscheduler Architecture and Performance in Computational Grid Environments
NASA Technical Reports Server (NTRS)
Shan, Hongzhang; Oliker, Leonid; Biswas, Rupak
2003-01-01
Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.
Redundancy management for efficient fault recovery in NASA's distributed computing system
NASA Technical Reports Server (NTRS)
Malek, Miroslaw; Pandya, Mihir; Yau, Kitty
1991-01-01
The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance.
Evaluation of the Intel iWarp parallel processor for space flight applications
NASA Technical Reports Server (NTRS)
Hine, Butler P., III; Fong, Terrence W.
1993-01-01
The potential of a DARPA-sponsored advanced processor, the Intel iWarp, for use in future SSF Data Management Systems (DMS) upgrades is evaluated through integration into the Ames DMS testbed and applications testing. The iWarp is a distributed, parallel computing system well suited for high performance computing applications such as matrix operations and image processing. The system architecture is modular, supports systolic and message-based computation, and is capable of providing massive computational power in a low-cost, low-power package. As a consequence, the iWarp offers significant potential for advanced space-based computing. This research seeks to determine the iWarp's suitability as a processing device for space missions. In particular, the project focuses on evaluating the ease of integrating the iWarp into the SSF DMS baseline architecture and the iWarp's ability to support computationally stressing applications representative of SSF tasks.
On the impact of approximate computation in an analog DeSTIN architecture.
Young, Steven; Lu, Junjie; Holleman, Jeremy; Arel, Itamar
2014-05-01
Deep machine learning (DML) holds the potential to revolutionize machine learning by automating rich feature extraction, which has become the primary bottleneck of human engineering in pattern recognition systems. However, the heavy computational burden renders DML systems implemented on conventional digital processors impractical for large-scale problems. The highly parallel computations required to implement large-scale deep learning systems are well suited to custom hardware. Analog computation has demonstrated power efficiency advantages of multiple orders of magnitude relative to digital systems while performing nonideal computations. In this paper, we investigate typical error sources introduced by analog computational elements and their impact on system-level performance in DeSTIN--a compositional deep learning architecture. These inaccuracies are evaluated on a pattern classification benchmark, clearly demonstrating the robustness of the underlying algorithm to the errors introduced by analog computational elements. A clear understanding of the impacts of nonideal computations is necessary to fully exploit the efficiency of analog circuits.
Creating executable architectures using Visual Simulation Objects (VSO)
NASA Astrophysics Data System (ADS)
Woodring, John W.; Comiskey, John B.; Petrov, Orlin M.; Woodring, Brian L.
2005-05-01
Investigations have been performed to identify a methodology for creating executable models of architectures and simulations of architecture that lead to an understanding of their dynamic properties. Colored Petri Nets (CPNs) are used to describe architecture because of their strong mathematical foundations, the existence of techniques for their verification and graph theory"s well-established history of success in modern science. CPNs have been extended to interoperate with legacy simulations via a High Level Architecture (HLA) compliant interface. It has also been demonstrated that an architecture created as a CPN can be integrated with Department of Defense Architecture Framework products to ensure consistency between static and dynamic descriptions. A computer-aided tool, Visual Simulation Objects (VSO), which aids analysts in specifying, composing and executing architectures, has been developed to verify the methodology and as a prototype commercial product.
Integrated command, control communication and computation system study
NASA Technical Reports Server (NTRS)
1981-01-01
The study was conducted in three phases: a functional requirements phase; a functional architecture phase; and a design plan phase. The major emphasis was on the functional architecture phase and the approaches used for its functional hierarchy, operations concept, and interfaces.
Roads towards fault-tolerant universal quantum computation
NASA Astrophysics Data System (ADS)
Campbell, Earl T.; Terhal, Barbara M.; Vuillot, Christophe
2017-09-01
A practical quantum computer must not merely store information, but also process it. To prevent errors introduced by noise from multiplying and spreading, a fault-tolerant computational architecture is required. Current experiments are taking the first steps toward noise-resilient logical qubits. But to convert these quantum devices from memories to processors, it is necessary to specify how a universal set of gates is performed on them. The leading proposals for doing so, such as magic-state distillation and colour-code techniques, have high resource demands. Alternative schemes, such as those that use high-dimensional quantum codes in a modular architecture, have potential benefits, but need to be explored further.
Roads towards fault-tolerant universal quantum computation.
Campbell, Earl T; Terhal, Barbara M; Vuillot, Christophe
2017-09-13
A practical quantum computer must not merely store information, but also process it. To prevent errors introduced by noise from multiplying and spreading, a fault-tolerant computational architecture is required. Current experiments are taking the first steps toward noise-resilient logical qubits. But to convert these quantum devices from memories to processors, it is necessary to specify how a universal set of gates is performed on them. The leading proposals for doing so, such as magic-state distillation and colour-code techniques, have high resource demands. Alternative schemes, such as those that use high-dimensional quantum codes in a modular architecture, have potential benefits, but need to be explored further.
NASA Astrophysics Data System (ADS)
Marukame, Takao; Nishi, Yoshifumi; Yasuda, Shin-ichi; Tanamoto, Tetsufumi
2018-04-01
The use of memristive devices for creating artificial neurons is promising for brain-inspired computing from the viewpoints of computation architecture and learning protocol. We present an energy-efficient multiplier accumulator based on a memristive array architecture incorporating both analog and digital circuitries. The analog circuitry is used to full advantage for neural networks, as demonstrated by the spike-timing-dependent plasticity (STDP) in fabricated AlO x /TiO x -based metal-oxide memristive devices. STDP protocols for controlling periodic analog resistance with long-range stability were experimentally verified using a variety of voltage amplitudes and spike timings.
Simulating motivated cognition
NASA Technical Reports Server (NTRS)
Gevarter, William B.
1991-01-01
A research effort to develop a sophisticated computer model of human behavior is described. A computer framework of motivated cognition was developed. Motivated cognition focuses on the motivations or affects that provide the context and drive in human cognition and decision making. A conceptual architecture of the human decision-making approach from the perspective of information processing in the human brain is developed in diagrammatic form. A preliminary version of such a diagram is presented. This architecture is then used as a vehicle for successfully constructing a computer program simulation Dweck and Leggett's findings that relate how an individual's implicit theories orient them toward particular goals, with resultant cognitions, affects, and behavior.
NASA Astrophysics Data System (ADS)
Benini, Luca
2017-06-01
The "internet of everything" envisions trillions of connected objects loaded with high-bandwidth sensors requiring massive amounts of local signal processing, fusion, pattern extraction and classification. From the computational viewpoint, the challenge is formidable and can be addressed only by pushing computing fabrics toward massive parallelism and brain-like energy efficiency levels. CMOS technology can still take us a long way toward this goal, but technology scaling is losing steam. Energy efficiency improvement will increasingly hinge on architecture, circuits, design techniques such as heterogeneous 3D integration, mixed-signal preprocessing, event-based approximate computing and non-Von-Neumann architectures for scalable acceleration.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Hsien-Hsin S
The overall objective of this research project is to develop novel architectural techniques as well as system software to achieve a highly secure and intrusion-tolerant computing system. Such system will be autonomous, self-adapting, introspective, with self-healing capability under the circumstances of improper operations, abnormal workloads, and malicious attacks. The scope of this research includes: (1) System-wide, unified introspection techniques for autonomic systems, (2) Secure information-flow microarchitecture, (3) Memory-centric security architecture, (4) Authentication control and its implication to security, (5) Digital right management, (5) Microarchitectural denial-of-service attacks on shared resources. During the period of the project, we developed several architectural techniquesmore » and system software for achieving a robust, secure, and reliable computing system toward our goal.« less
Differential geometric treewidth estimation in adiabatic quantum computation
NASA Astrophysics Data System (ADS)
Wang, Chi; Jonckheere, Edmond; Brun, Todd
2016-10-01
The D-Wave adiabatic quantum computing platform is designed to solve a particular class of problems—the Quadratic Unconstrained Binary Optimization (QUBO) problems. Due to the particular "Chimera" physical architecture of the D-Wave chip, the logical problem graph at hand needs an extra process called minor embedding in order to be solvable on the D-Wave architecture. The latter problem is itself NP-hard. In this paper, we propose a novel polynomial-time approximation to the closely related treewidth based on the differential geometric concept of Ollivier-Ricci curvature. The latter runs in polynomial time and thus could significantly reduce the overall complexity of determining whether a QUBO problem is minor embeddable, and thus solvable on the D-Wave architecture.
Thrifty: An Exascale Architecture for Energy Proportional Computing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Torrellas, Josep
2014-12-23
The objective of this project is to design different aspects of a novel exascale architecture called Thrifty. Our goal is to focus on the challenges of power/energy efficiency, performance, and resiliency in exascale systems. The project includes work on computer architecture (Josep Torrellas from University of Illinois), compilation (Daniel Quinlan from Lawrence Livermore National Laboratory), runtime and applications (Laura Carrington from University of California San Diego), and circuits (Wilfred Pinfold from Intel Corporation). In this report, we focus on the progress at the University of Illinois during the last year of the grant (September 1, 2013 to August 31, 2014).more » We also point to the progress in the other collaborating institutions when needed.« less
Local Alignment Tool Based on Hadoop Framework and GPU Architecture
Hung, Che-Lun; Hua, Guan-Jie
2014-01-01
With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biologists to compare protein sequences. To deal with the big biology data, it is hard to rely on single GPU. Therefore, we implement a distributed BLASTP by combining Hadoop and multi-GPUs. The experimental results present that the proposed method can improve the performance of BLASTP on single GPU, and also it can achieve high availability and fault tolerance. PMID:24955362
Local alignment tool based on Hadoop framework and GPU architecture.
Hung, Che-Lun; Hua, Guan-Jie
2014-01-01
With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biologists to compare protein sequences. To deal with the big biology data, it is hard to rely on single GPU. Therefore, we implement a distributed BLASTP by combining Hadoop and multi-GPUs. The experimental results present that the proposed method can improve the performance of BLASTP on single GPU, and also it can achieve high availability and fault tolerance.
Authentication and Authorization of End User in Microservice Architecture
NASA Astrophysics Data System (ADS)
He, Xiuyu; Yang, Xudong
2017-10-01
As the market and business continues to expand; the traditional single monolithic architecture is facing more and more challenges. The development of cloud computing and container technology promote microservice architecture became more popular. While the low coupling, fine granularity, scalability, flexibility and independence of the microservice architecture bring convenience, the inherent complexity of the distributed system make the security of microservice architecture important and difficult. This paper aims to study the authentication and authorization of the end user under the microservice architecture. By comparing with the traditional measures and researching on existing technology, this paper put forward a set of authentication and authorization strategies suitable for microservice architecture, such as distributed session, SSO solutions, client-side JSON web token and JWT + API Gateway, and summarize the advantages and disadvantages of each method.
NASA Astrophysics Data System (ADS)
Lee, J.; Kim, K.
A Very Large Scale Integration (VLSI) architecture for robot direct kinematic computation suitable for industrial robot manipulators was investigated. The Denavit-Hartenberg transformations are reviewed to exploit a proper processing element, namely an augmented CORDIC. Specifically, two distinct implementations are elaborated on, such as the bit-serial and parallel. Performance of each scheme is analyzed with respect to the time to compute one location of the end-effector of a 6-links manipulator, and the number of transistors required.
ERIC Educational Resources Information Center
Hill, Linda L.; Crosier, Scott J.; Smith, Terrence R.; Goodchild, Michael; Iannella, Renato; Erickson, John S.; Reich, Vicky; Rosenthal, David S. H.
2001-01-01
Includes five articles. Topics include requirements for a content standard to describe computational models; architectures for digital rights management systems; access control for digital information objects; LOCKSS (Lots of Copies Keep Stuff Safe) that allows libraries to run Web caches for specific journals; and a Web site from the U.S.…
1984-04-01
Scientific- Architecture 4% 4% Technical Computer Sci 38% 37% Math 40% 40% Meteorology 6% 6% Physics 12 % 13% Nontechnical Quality Freeflow 2/ Quality...Architecture 4 Computer Sci 48 43 40 Math 30 35 38 Meteorology 6 6 6 Physics 12 12 12 Engineer Electrical 40% 50% 50% Aero Group 25 25 30 Other / 35 25 20...with Technical Degrees by Major Weapon System. . . 12 FIGURE 4 - Pilots with Technical Degrees by Category . . . . . . 13 FIGURE 5 - Regression
CERN's Common Unix and X Terminal Environment
NASA Astrophysics Data System (ADS)
Cass, Tony
The Desktop Infrastructure Group of CERN's Computing and Networks Division has developed a Common Unix and X Terminal Environment to ease the migration to Unix based Interactive Computing. The CUTE architecture relies on a distributed filesystem—currently Trans arc's AFS—to enable essentially interchangeable client work-stations to access both "home directory" and program files transparently. Additionally, we provide a suite of programs to configure workstations for CUTE and to ensure continued compatibility. This paper describes the different components and the development of the CUTE architecture.
Integrating Software Modules For Robot Control
NASA Technical Reports Server (NTRS)
Volpe, Richard A.; Khosla, Pradeep; Stewart, David B.
1993-01-01
Reconfigurable, sensor-based control system uses state variables in systematic integration of reusable control modules. Designed for open-architecture hardware including many general-purpose microprocessors, each having own local memory plus access to global shared memory. Implemented in software as extension of Chimera II real-time operating system. Provides transparent computing mechanism for intertask communication between control modules and generic process-module architecture for multiprocessor realtime computation. Used to control robot arm. Proves useful in variety of other control and robotic applications.
NASA Technical Reports Server (NTRS)
Lee, J.; Kim, K.
1991-01-01
A Very Large Scale Integration (VLSI) architecture for robot direct kinematic computation suitable for industrial robot manipulators was investigated. The Denavit-Hartenberg transformations are reviewed to exploit a proper processing element, namely an augmented CORDIC. Specifically, two distinct implementations are elaborated on, such as the bit-serial and parallel. Performance of each scheme is analyzed with respect to the time to compute one location of the end-effector of a 6-links manipulator, and the number of transistors required.
A Parallel Trade Study Architecture for Design Optimization of Complex Systems
NASA Technical Reports Server (NTRS)
Kim, Hongman; Mullins, James; Ragon, Scott; Soremekun, Grant; Sobieszczanski-Sobieski, Jaroslaw
2005-01-01
Design of a successful product requires evaluating many design alternatives in a limited design cycle time. This can be achieved through leveraging design space exploration tools and available computing resources on the network. This paper presents a parallel trade study architecture to integrate trade study clients and computing resources on a network using Web services. The parallel trade study solution is demonstrated to accelerate design of experiments, genetic algorithm optimization, and a cost as an independent variable (CAIV) study for a space system application.
2008-03-01
computational version of the CASIE architecture serves to demonstrate the functionality of our primary theories. However, implementation of several other...following facts. First, based on Theorem 3 and Theorem 5, the objective function is non -increasing under updating rule (6); second, by the criteria for...reassignment in updating rule (7), it is trivial to show that the objective function is non -increasing under updating rule (7). A Unified View to Graph
COMBAT: mobile-Cloud-based cOmpute/coMmunications infrastructure for BATtlefield applications
NASA Astrophysics Data System (ADS)
Soyata, Tolga; Muraleedharan, Rajani; Langdon, Jonathan; Funai, Colin; Ames, Scott; Kwon, Minseok; Heinzelman, Wendi
2012-05-01
The amount of data processed annually over the Internet has crossed the zetabyte boundary, yet this Big Data cannot be efficiently processed or stored using today's mobile devices. Parallel to this explosive growth in data, a substantial increase in mobile compute-capability and the advances in cloud computing have brought the state-of-the- art in mobile-cloud computing to an inflection point, where the right architecture may allow mobile devices to run applications utilizing Big Data and intensive computing. In this paper, we propose the MObile Cloud-based Hybrid Architecture (MOCHA), which formulates a solution to permit mobile-cloud computing applications such as object recognition in the battlefield by introducing a mid-stage compute- and storage-layer, called the cloudlet. MOCHA is built on the key observation that many mobile-cloud applications have the following characteristics: 1) they are compute-intensive, requiring the compute-power of a supercomputer, and 2) they use Big Data, requiring a communications link to cloud-based database sources in near-real-time. In this paper, we describe the operation of MOCHA in battlefield applications, by formulating the aforementioned mobile and cloudlet to be housed within a soldier's vest and inside a military vehicle, respectively, and enabling access to the cloud through high latency satellite links. We provide simulations using the traditional mobile-cloud approach as well as utilizing MOCHA with a mid-stage cloudlet to quantify the utility of this architecture. We show that the MOCHA platform for mobile-cloud computing promises a future for critical battlefield applications that access Big Data, which is currently not possible using existing technology.
Bespoke physics for living technology.
Ackley, David H
2013-01-01
In the physics of the natural world, basic tasks of life, such as homeostasis and reproduction, are extremely complex operations, requiring the coordination of billions of atoms even in simple cases. By contrast, artificial living organisms can be implemented in computers using relatively few bits, and copying a data structure is trivial. Of course, the physical overheads of the computers themselves are huge, but since their programmability allows digital "laws of physics" to be tailored like a custom suit, deploying living technology atop an engineered computational substrate might be as or more effective than building directly on the natural laws of physics, for a substantial range of desirable purposes. This article suggests basic criteria and metrics for bespoke physics computing architectures, describes one such architecture, and offers data and illustrations of custom living technology competing to reproduce while collaborating on an externally useful computation.
The Montage architecture for grid-enabled science processing of large, distributed datasets
NASA Technical Reports Server (NTRS)
Jacob, Joseph C.; Katz, Daniel S .; Prince, Thomas; Berriman, Bruce G.; Good, John C.; Laity, Anastasia C.; Deelman, Ewa; Singh, Gurmeet; Su, Mei-Hui
2004-01-01
Montage is an Earth Science Technology Office (ESTO) Computational Technologies (CT) Round III Grand Challenge investigation to deploy a portable, compute-intensive, custom astronomical image mosaicking service for the National Virtual Observatory (NVO). Although Montage is developing a compute- and data-intensive service for the astronomy community, we are also helping to address a problem that spans both Earth and Space science, namely how to efficiently access and process multi-terabyte, distributed datasets. In both communities, the datasets are massive, and are stored in distributed archives that are, in most cases, remote from the available Computational resources. Therefore, state of the art computational grid technologies are a key element of the Montage portal architecture. This paper describes the aspects of the Montage design that are applicable to both the Earth and Space science communities.
Plagianakos, V P; Magoulas, G D; Vrahatis, M N
2006-03-01
Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of lesions in colonoscopy. Our approach is based on partitioning the training set across multiple processors using a parallel virtual machine. In this way, interconnected computers of varied architectures can be used for the distributed evaluation of the error function and gradient values, and, thus, training neural networks utilizing various learning methods. The proposed methodology has large granularity and low synchronization, and has been implemented and tested. Our results indicate that the parallel virtual machine implementation of the training algorithms developed leads to considerable speedup, especially when large network architectures and training sets are used.
Molecular Sticker Model Stimulation on Silicon for a Maximum Clique Problem
Ning, Jianguo; Li, Yanmei; Yu, Wen
2015-01-01
Molecular computers (also called DNA computers), as an alternative to traditional electronic computers, are smaller in size but more energy efficient, and have massive parallel processing capacity. However, DNA computers may not outperform electronic computers owing to their higher error rates and some limitations of the biological laboratory. The stickers model, as a typical DNA-based computer, is computationally complete and universal, and can be viewed as a bit-vertically operating machine. This makes it attractive for silicon implementation. Inspired by the information processing method on the stickers computer, we propose a novel parallel computing model called DEM (DNA Electronic Computing Model) on System-on-a-Programmable-Chip (SOPC) architecture. Except for the significant difference in the computing medium—transistor chips rather than bio-molecules—the DEM works similarly to DNA computers in immense parallel information processing. Additionally, a plasma display panel (PDP) is used to show the change of solutions, and helps us directly see the distribution of assignments. The feasibility of the DEM is tested by applying it to compute a maximum clique problem (MCP) with eight vertices. Owing to the limited computing sources on SOPC architecture, the DEM could solve moderate-size problems in polynomial time. PMID:26075867
Elastic Cloud Computing Architecture and System for Heterogeneous Spatiotemporal Computing
NASA Astrophysics Data System (ADS)
Shi, X.
2017-10-01
Spatiotemporal computation implements a variety of different algorithms. When big data are involved, desktop computer or standalone application may not be able to complete the computation task due to limited memory and computing power. Now that a variety of hardware accelerators and computing platforms are available to improve the performance of geocomputation, different algorithms may have different behavior on different computing infrastructure and platforms. Some are perfect for implementation on a cluster of graphics processing units (GPUs), while GPUs may not be useful on certain kind of spatiotemporal computation. This is the same situation in utilizing a cluster of Intel's many-integrated-core (MIC) or Xeon Phi, as well as Hadoop or Spark platforms, to handle big spatiotemporal data. Furthermore, considering the energy efficiency requirement in general computation, Field Programmable Gate Array (FPGA) may be a better solution for better energy efficiency when the performance of computation could be similar or better than GPUs and MICs. It is expected that an elastic cloud computing architecture and system that integrates all of GPUs, MICs, and FPGAs could be developed and deployed to support spatiotemporal computing over heterogeneous data types and computational problems.
Optical memories in digital computing
NASA Technical Reports Server (NTRS)
Alford, C. O.; Gaylord, T. K.
1979-01-01
High capacity optical memories with relatively-high data-transfer rate and multiport simultaneous access capability may serve as basis for new computer architectures. Several computer structures that might profitably use memories are: a) simultaneous record-access system, b) simultaneously-shared memory computer system, and c) parallel digital processing structure.
From photons to big-data applications: terminating terabits
2016-01-01
Computer architectures have entered a watershed as the quantity of network data generated by user applications exceeds the data-processing capacity of any individual computer end-system. It will become impossible to scale existing computer systems while a gap grows between the quantity of networked data and the capacity for per system data processing. Despite this, the growth in demand in both task variety and task complexity continues unabated. Networked computer systems provide a fertile environment in which new applications develop. As networked computer systems become akin to infrastructure, any limitation upon the growth in capacity and capabilities becomes an important constraint of concern to all computer users. Considering a networked computer system capable of processing terabits per second, as a benchmark for scalability, we critique the state of the art in commodity computing, and propose a wholesale reconsideration in the design of computer architectures and their attendant ecosystem. Our proposal seeks to reduce costs, save power and increase performance in a multi-scale approach that has potential application from nanoscale to data-centre-scale computers. PMID:26809573
From photons to big-data applications: terminating terabits.
Zilberman, Noa; Moore, Andrew W; Crowcroft, Jon A
2016-03-06
Computer architectures have entered a watershed as the quantity of network data generated by user applications exceeds the data-processing capacity of any individual computer end-system. It will become impossible to scale existing computer systems while a gap grows between the quantity of networked data and the capacity for per system data processing. Despite this, the growth in demand in both task variety and task complexity continues unabated. Networked computer systems provide a fertile environment in which new applications develop. As networked computer systems become akin to infrastructure, any limitation upon the growth in capacity and capabilities becomes an important constraint of concern to all computer users. Considering a networked computer system capable of processing terabits per second, as a benchmark for scalability, we critique the state of the art in commodity computing, and propose a wholesale reconsideration in the design of computer architectures and their attendant ecosystem. Our proposal seeks to reduce costs, save power and increase performance in a multi-scale approach that has potential application from nanoscale to data-centre-scale computers. © 2016 The Authors.
FPGA-Based, Self-Checking, Fault-Tolerant Computers
NASA Technical Reports Server (NTRS)
Some, Raphael; Rennels, David
2004-01-01
A proposed computer architecture would exploit the capabilities of commercially available field-programmable gate arrays (FPGAs) to enable computers to detect and recover from bit errors. The main purpose of the proposed architecture is to enable fault-tolerant computing in the presence of single-event upsets (SEUs). [An SEU is a spurious bit flip (also called a soft error) caused by a single impact of ionizing radiation.] The architecture would also enable recovery from some soft errors caused by electrical transients and, to some extent, from intermittent and permanent (hard) errors caused by aging of electronic components. A typical FPGA of the current generation contains one or more complete processor cores, memories, and highspeed serial input/output (I/O) channels, making it possible to shrink a board-level processor node to a single integrated-circuit chip. Custom, highly efficient microcontrollers, general-purpose computers, custom I/O processors, and signal processors can be rapidly and efficiently implemented by use of FPGAs. Unfortunately, FPGAs are susceptible to SEUs. Prior efforts to mitigate the effects of SEUs have yielded solutions that degrade performance of the system and require support from external hardware and software. In comparison with other fault-tolerant- computing architectures (e.g., triple modular redundancy), the proposed architecture could be implemented with less circuitry and lower power demand. Moreover, the fault-tolerant computing functions would require only minimal support from circuitry outside the central processing units (CPUs) of computers, would not require any software support, and would be largely transparent to software and to other computer hardware. There would be two types of modules: a self-checking processor module and a memory system (see figure). The self-checking processor module would be implemented on a single FPGA and would be capable of detecting its own internal errors. It would contain two CPUs executing identical programs in lock step, with comparison of their outputs to detect errors. It would also contain various cache local memory circuits, communication circuits, and configurable special-purpose processors that would use self-checking checkers. (The basic principle of the self-checking checker method is to utilize logic circuitry that generates error signals whenever there is an error in either the checker or the circuit being checked.) The memory system would comprise a main memory and a hardware-controlled check-pointing system (CPS) based on a buffer memory denoted the recovery cache. The main memory would contain random-access memory (RAM) chips and FPGAs that would, in addition to everything else, implement double-error-detecting and single-error-correcting memory functions to enable recovery from single-bit errors.
ERIC Educational Resources Information Center
McCartney, Robert; Tenenberg, Josh
2008-01-01
Some have proposed that realistic problem situations are better for learning. This issue contains two articles that examine the effects of "making it real" in computer architecture and human-computer interaction.
NASA Astrophysics Data System (ADS)
Fabien-Ouellet, Gabriel; Gloaguen, Erwan; Giroux, Bernard
2017-03-01
Full Waveform Inversion (FWI) aims at recovering the elastic parameters of the Earth by matching recordings of the ground motion with the direct solution of the wave equation. Modeling the wave propagation for realistic scenarios is computationally intensive, which limits the applicability of FWI. The current hardware evolution brings increasing parallel computing power that can speed up the computations in FWI. However, to take advantage of the diversity of parallel architectures presently available, new programming approaches are required. In this work, we explore the use of OpenCL to develop a portable code that can take advantage of the many parallel processor architectures now available. We present a program called SeisCL for 2D and 3D viscoelastic FWI in the time domain. The code computes the forward and adjoint wavefields using finite-difference and outputs the gradient of the misfit function given by the adjoint state method. To demonstrate the code portability on different architectures, the performance of SeisCL is tested on three different devices: Intel CPUs, NVidia GPUs and Intel Xeon PHI. Results show that the use of GPUs with OpenCL can speed up the computations by nearly two orders of magnitudes over a single threaded application on the CPU. Although OpenCL allows code portability, we show that some device-specific optimization is still required to get the best performance out of a specific architecture. Using OpenCL in conjunction with MPI allows the domain decomposition of large models on several devices located on different nodes of a cluster. For large enough models, the speedup of the domain decomposition varies quasi-linearly with the number of devices. Finally, we investigate two different approaches to compute the gradient by the adjoint state method and show the significant advantages of using OpenCL for FWI.
NASA Technical Reports Server (NTRS)
LaValley, Brian W.; Little, Phillip D.; Walter, Chris J.
2011-01-01
This report documents the capabilities of the EDICT tools for error modeling and error propagation analysis when operating with models defined in the Architecture Analysis & Design Language (AADL). We discuss our experience using the EDICT error analysis capabilities on a model of the Scalable Processor-Independent Design for Enhanced Reliability (SPIDER) architecture that uses the Reliable Optical Bus (ROBUS). Based on these experiences we draw some initial conclusions about model based design techniques for error modeling and analysis of highly reliable computing architectures.
Petri net model for analysis of concurrently processed complex algorithms
NASA Technical Reports Server (NTRS)
Stoughton, John W.; Mielke, Roland R.
1986-01-01
This paper presents a Petri-net model suitable for analyzing the concurrent processing of computationally complex algorithms. The decomposed operations are to be processed in a multiple processor, data driven architecture. Of particular interest is the application of the model to both the description of the data/control flow of a particular algorithm, and to the general specification of the data driven architecture. A candidate architecture is also presented.
Information Architecture: Notes toward a New Curriculum.
ERIC Educational Resources Information Center
Latham, Don
2002-01-01
Considers the evolution of information architectures as a field of professional education. Topics include the need for an interdisciplinary approach; balancing practical skills with theoretical concepts; and key content areas, including information organization, graphic design, computer science, user and usability studies, and communication.…
Architectural requirements for the Red Storm computing system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Camp, William J.; Tomkins, James Lee
This report is based on the Statement of Work (SOW) describing the various requirements for delivering 3 new supercomputer system to Sandia National Laboratories (Sandia) as part of the Department of Energy's (DOE) Accelerated Strategic Computing Initiative (ASCI) program. This system is named Red Storm and will be a distributed memory, massively parallel processor (MPP) machine built primarily out of commodity parts. The requirements presented here distill extensive architectural and design experience accumulated over a decade and a half of research, development and production operation of similar machines at Sandia. Red Storm will have an unusually high bandwidth, low latencymore » interconnect, specially designed hardware and software reliability features, a light weight kernel compute node operating system and the ability to rapidly switch major sections of the machine between classified and unclassified computing environments. Particular attention has been paid to architectural balance in the design of Red Storm, and it is therefore expected to achieve an atypically high fraction of its peak speed of 41 TeraOPS on real scientific computing applications. In addition, Red Storm is designed to be upgradeable to many times this initial peak capability while still retaining appropriate balance in key design dimensions. Installation of the Red Storm computer system at Sandia's New Mexico site is planned for 2004, and it is expected that the system will be operated for a minimum of five years following installation.« less
A Standard Platform for Testing and Comparison of MDAO Architectures
NASA Technical Reports Server (NTRS)
Gray, Justin S.; Moore, Kenneth T.; Hearn, Tristan A.; Naylor, Bret A.
2012-01-01
The Multidisciplinary Design Analysis and Optimization (MDAO) community has developed a multitude of algorithms and techniques, called architectures, for performing optimizations on complex engineering systems which involve coupling between multiple discipline analyses. These architectures seek to efficiently handle optimizations with computationally expensive analyses including multiple disciplines. We propose a new testing procedure that can provide a quantitative and qualitative means of comparison among architectures. The proposed test procedure is implemented within the open source framework, OpenMDAO, and comparative results are presented for five well-known architectures: MDF, IDF, CO, BLISS, and BLISS-2000. We also demonstrate how using open source soft- ware development methods can allow the MDAO community to submit new problems and architectures to keep the test suite relevant.
Design and Verification of Remote Sensing Image Data Center Storage Architecture Based on Hadoop
NASA Astrophysics Data System (ADS)
Tang, D.; Zhou, X.; Jing, Y.; Cong, W.; Li, C.
2018-04-01
The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.
Computer aided design of architecture of degradable tissue engineering scaffolds.
Heljak, M K; Kurzydlowski, K J; Swieszkowski, W
2017-11-01
One important factor affecting the process of tissue regeneration is scaffold stiffness loss, which should be properly balanced with the rate of tissue regeneration. The aim of the research reported here was to develop a computer tool for designing the architecture of biodegradable scaffolds fabricated by melt-dissolution deposition systems (e.g. Fused Deposition Modeling) to provide the required scaffold stiffness at each stage of degradation/regeneration. The original idea presented in the paper is that the stiffness of a tissue engineering scaffold can be controlled during degradation by means of a proper selection of the diameter of the constituent fibers and the distances between them. This idea is based on the size-effect on degradation of aliphatic polyesters. The presented computer tool combines a genetic algorithm and a diffusion-reaction model of polymer hydrolytic degradation. In particular, we show how to design the architecture of scaffolds made of poly(DL-lactide-co-glycolide) with the required Young's modulus change during hydrolytic degradation.
Power and Performance Trade-offs for Space Time Adaptive Processing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gawande, Nitin A.; Manzano Franco, Joseph B.; Tumeo, Antonino
Computational efficiency – performance relative to power or energy – is one of the most important concerns when designing RADAR processing systems. This paper analyzes power and performance trade-offs for a typical Space Time Adaptive Processing (STAP) application. We study STAP implementations for CUDA and OpenMP on two computationally efficient architectures, Intel Haswell Core I7-4770TE and NVIDIA Kayla with a GK208 GPU. We analyze the power and performance of STAP’s computationally intensive kernels across the two hardware testbeds. We also show the impact and trade-offs of GPU optimization techniques. We show that data parallelism can be exploited for efficient implementationmore » on the Haswell CPU architecture. The GPU architecture is able to process large size data sets without increase in power requirement. The use of shared memory has a significant impact on the power requirement for the GPU. A balance between the use of shared memory and main memory access leads to an improved performance in a typical STAP application.« less
Automated problem scheduling and reduction of synchronization delay effects
NASA Technical Reports Server (NTRS)
Saltz, Joel H.
1987-01-01
It is anticipated that in order to make effective use of many future high performance architectures, programs will have to exhibit at least a medium grained parallelism. A framework is presented for partitioning very sparse triangular systems of linear equations that is designed to produce favorable preformance results in a wide variety of parallel architectures. Efficient methods for solving these systems are of interest because: (1) they provide a useful model problem for use in exploring heuristics for the aggregation, mapping and scheduling of relatively fine grained computations whose data dependencies are specified by directed acrylic graphs, and (2) because such efficient methods can find direct application in the development of parallel algorithms for scientific computation. Simple expressions are derived that describe how to schedule computational work with varying degrees of granularity. The Encore Multimax was used as a hardware simulator to investigate the performance effects of using the partitioning techniques presented in shared memory architectures with varying relative synchronization costs.
Colt: an experiment in wormhole run-time reconfiguration
NASA Astrophysics Data System (ADS)
Bittner, Ray; Athanas, Peter M.; Musgrove, Mark
1996-10-01
Wormhole run-time reconfiguration (RTR) is an attempt to create a refined computing paradigm for high performance computational tasks. By combining concepts from field programmable gate array (FPGA) technologies with data flow computing, the Colt/Stallion architecture achieves high utilization of hardware resources, and facilitates rapid run-time reconfiguration. Targeted mainly at DSP-type operations, the Colt integrated circuit -- a prototype wormhole RTR device -- compares favorably to contemporary DSP alternatives in terms of silicon area consumed per unit computation and in computing performance. Although emphasis has been placed on signal processing applications, general purpose computation has not been overlooked. Colt is a prototype that defines an architecture not only at the chip level but also in terms of an overall system design. As this system is realized, the concept of wormhole RTR will be applied to numerical computation and DSP applications including those common to image processing, communications systems, digital filters, acoustic processing, real-time control systems and simulation acceleration.
Multi-threaded ATLAS simulation on Intel Knights Landing processors
NASA Astrophysics Data System (ADS)
Farrell, Steven; Calafiura, Paolo; Leggett, Charles; Tsulaia, Vakhtang; Dotti, Andrea; ATLAS Collaboration
2017-10-01
The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), was delivered to its users in two phases with the first phase online at the end of 2015 and the second phase now online at the end of 2016. Cori Phase 2 is based on the KNL architecture and contains over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a good potential use-case for the KNL architecture and supercomputers like Cori. ATLAS simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this paper we will give an overview of the ATLAS simulation application with details on its multi-threaded design. Then, we will present a performance analysis of the application on KNL devices and compare it to a traditional x86 platform to demonstrate the capabilities of the architecture and evaluate the benefits of utilizing KNL platforms like Cori for ATLAS production.
Hybrid techniques for the digital control of mechanical and optical systems
NASA Astrophysics Data System (ADS)
Acernese, Fausto; Barone, Fabrizio; De Rosa, Rosario; Eleuteri, Antonio; Milano, Leopoldo; Pardi, Silvio; Ricciardi, Iolanda; Russo, Guido
2004-07-01
One of the main requirements of a digital system for the control of interferometric detectors of gravitational waves is the computing power, that is a direct consequence of the increasing complexity of the digital algorithms necessary for the control signals generation. For this specific task many specialised non standard real-time architectures have been developed, often very expensive and difficult to upgrade. On the other hand, such computing power is generally fully available for off-line applications on standard Pc based systems. Therefore, a possible and obvious solution may be provided by the integration of both the the real-time and off-line architecture resulting in a hybrid control system architecture based on standards available components, trying to get both the advantages of the perfect data synchronization provided by the real-time systems and by the large computing power available on Pc based systems. Such integration may be provided by the implementation of the link between the two different architectures through the standard Ethernet network, whose data transfer speed is largely increasing in these years, using the TCP/IP and UDP protocols. In this paper we describe the architecture of an hybrid Ethernet based real-time control system protoype we implemented in Napoli, discussing its characteristics and performances. Finally we discuss a possible application to the real-time control of a suspended mass of the mode cleaner of the 3m prototype optical interferometer for gravitational wave detection (IDGW-3P) operational in Napoli.
WATERLOPP V2/64: A highly parallel machine for numerical computation
NASA Astrophysics Data System (ADS)
Ostlund, Neil S.
1985-07-01
Current technological trends suggest that the high performance scientific machines of the future are very likely to consist of a large number (greater than 1024) of processors connected and communicating with each other in some as yet undetermined manner. Such an assembly of processors should behave as a single machine in obtaining numerical solutions to scientific problems. However, the appropriate way of organizing both the hardware and software of such an assembly of processors is an unsolved and active area of research. It is particularly important to minimize the organizational overhead of interprocessor comunication, global synchronization, and contention for shared resources if the performance of a large number ( n) of processors is to be anything like the desirable n times the performance of a single processor. In many situations, adding a processor actually decreases the performance of the overall system since the extra organizational overhead is larger than the extra processing power added. The systolic loop architecture is a new multiple processor architecture which attemps at a solution to the problem of how to organize a large number of asynchronous processors into an effective computational system while minimizing the organizational overhead. This paper gives a brief overview of the basic systolic loop architecture, systolic loop algorithms for numerical computation, and a 64-processor implementation of the architecture, WATERLOOP V2/64, that is being used as a testbed for exploring the hardware, software, and algorithmic aspects of the architecture.
Securing the Data Storage and Processing in Cloud Computing Environment
ERIC Educational Resources Information Center
Owens, Rodney
2013-01-01
Organizations increasingly utilize cloud computing architectures to reduce costs and energy consumption both in the data warehouse and on mobile devices by better utilizing the computing resources available. However, the security and privacy issues with publicly available cloud computing infrastructures have not been studied to a sufficient depth…
Can the Computer Design a School Building?
ERIC Educational Resources Information Center
Roberts, Charles
The implications of computer technology and architecture are discussed with reference to school building design. A brief introduction is given of computer applications in other fields leading to the conclusions that computers alone cannot design school buildings but may serve as a useful tool in the overall design process. Specific examples are…
Fast underdetermined BSS architecture design methodology for real time applications.
Mopuri, Suresh; Reddy, P Sreenivasa; Acharyya, Amit; Naik, Ganesh R
2015-01-01
In this paper, we propose a high speed architecture design methodology for the Under-determined Blind Source Separation (UBSS) algorithm using our recently proposed high speed Discrete Hilbert Transform (DHT) targeting real time applications. In UBSS algorithm, unlike the typical BSS, the number of sensors are less than the number of the sources, which is of more interest in the real time applications. The DHT architecture has been implemented based on sub matrix multiplication method to compute M point DHT, which uses N point architecture recursively and where M is an integer multiples of N. The DHT architecture and state of the art architecture are coded in VHDL for 16 bit word length and ASIC implementation is carried out using UMC 90 - nm technology @V DD = 1V and @ 1MHZ clock frequency. The proposed architecture implementation and experimental comparison results show that the DHT design is two times faster than state of the art architecture.
Integration of nanoscale memristor synapses in neuromorphic computing architectures
NASA Astrophysics Data System (ADS)
Indiveri, Giacomo; Linares-Barranco, Bernabé; Legenstein, Robert; Deligeorgis, George; Prodromakis, Themistoklis
2013-09-01
Conventional neuro-computing architectures and artificial neural networks have often been developed with no or loose connections to neuroscience. As a consequence, they have largely ignored key features of biological neural processing systems, such as their extremely low-power consumption features or their ability to carry out robust and efficient computation using massively parallel arrays of limited precision, highly variable, and unreliable components. Recent developments in nano-technologies are making available extremely compact and low power, but also variable and unreliable solid-state devices that can potentially extend the offerings of availing CMOS technologies. In particular, memristors are regarded as a promising solution for modeling key features of biological synapses due to their nanoscale dimensions, their capacity to store multiple bits of information per element and the low energy required to write distinct states. In this paper, we first review the neuro- and neuromorphic computing approaches that can best exploit the properties of memristor and scale devices, and then propose a novel hybrid memristor-CMOS neuromorphic circuit which represents a radical departure from conventional neuro-computing approaches, as it uses memristors to directly emulate the biophysics and temporal dynamics of real synapses. We point out the differences between the use of memristors in conventional neuro-computing architectures and the hybrid memristor-CMOS circuit proposed, and argue how this circuit represents an ideal building block for implementing brain-inspired probabilistic computing paradigms that are robust to variability and fault tolerant by design.
NASA Astrophysics Data System (ADS)
Tekin, Tolga; Töpper, Michael; Reichl, Herbert
2009-05-01
Technological frontiers between semiconductor technology, packaging, and system design are disappearing. Scaling down geometries [1] alone does not provide improvement of performance, less power, smaller size, and lower cost. It will require "More than Moore" [2] through the tighter integration of system level components at the package level. System-in-Package (SiP) will deliver the efficient use of three dimensions (3D) through innovation in packaging and interconnect technology. A key bottleneck to the implementation of high-performance microelectronic systems, including SiP, is the lack of lowlatency, high-bandwidth, and high density off-chip interconnects. Some of the challenges in achieving high-bandwidth chip-to-chip communication using electrical interconnects include the high losses in the substrate dielectric, reflections and impedance discontinuities, and susceptibility to crosstalk [3]. Obviously, the incentive for the use of photonics to overcome the challenges and leverage low-latency and highbandwidth communication will enable the vision of optical computing within next generation architectures. Supercomputers of today offer sustained performance of more than petaflops, which can be increased by utilizing optical interconnects. Next generation computing architectures are needed with ultra low power consumption; ultra high performance with novel interconnection technologies. In this paper we will discuss a CMOS compatible underlying technology to enable next generation optical computing architectures. By introducing a new optical layer within the 3D SiP, the development of converged microsystems, deployment for next generation optical computing architecture will be leveraged.
A direct-to-drive neural data acquisition system.
Kinney, Justin P; Bernstein, Jacob G; Meyer, Andrew J; Barber, Jessica B; Bolivar, Marti; Newbold, Bryan; Scholvin, Jorg; Moore-Kochlacs, Caroline; Wentz, Christian T; Kopell, Nancy J; Boyden, Edward S
2015-01-01
Driven by the increasing channel count of neural probes, there is much effort being directed to creating increasingly scalable electrophysiology data acquisition (DAQ) systems. However, all such systems still rely on personal computers for data storage, and thus are limited by the bandwidth and cost of the computers, especially as the scale of recording increases. Here we present a novel architecture in which a digital processor receives data from an analog-to-digital converter, and writes that data directly to hard drives, without the need for a personal computer to serve as an intermediary in the DAQ process. This minimalist architecture may support exceptionally high data throughput, without incurring costs to support unnecessary hardware and overhead associated with personal computers, thus facilitating scaling of electrophysiological recording in the future.
A direct-to-drive neural data acquisition system
Kinney, Justin P.; Bernstein, Jacob G.; Meyer, Andrew J.; Barber, Jessica B.; Bolivar, Marti; Newbold, Bryan; Scholvin, Jorg; Moore-Kochlacs, Caroline; Wentz, Christian T.; Kopell, Nancy J.; Boyden, Edward S.
2015-01-01
Driven by the increasing channel count of neural probes, there is much effort being directed to creating increasingly scalable electrophysiology data acquisition (DAQ) systems. However, all such systems still rely on personal computers for data storage, and thus are limited by the bandwidth and cost of the computers, especially as the scale of recording increases. Here we present a novel architecture in which a digital processor receives data from an analog-to-digital converter, and writes that data directly to hard drives, without the need for a personal computer to serve as an intermediary in the DAQ process. This minimalist architecture may support exceptionally high data throughput, without incurring costs to support unnecessary hardware and overhead associated with personal computers, thus facilitating scaling of electrophysiological recording in the future. PMID:26388740
Apparatuses and Methods for Producing Runtime Architectures of Computer Program Modules
NASA Technical Reports Server (NTRS)
Abi-Antoun, Marwan Elia (Inventor); Aldrich, Jonathan Erik (Inventor)
2013-01-01
Apparatuses and methods for producing run-time architectures of computer program modules. One embodiment includes creating an abstract graph from the computer program module and from containment information corresponding to the computer program module, wherein the abstract graph has nodes including types and objects, and wherein the abstract graph relates an object to a type, and wherein for a specific object the abstract graph relates the specific object to a type containing the specific object; and creating a runtime graph from the abstract graph, wherein the runtime graph is a representation of the true runtime object graph, wherein the runtime graph represents containment information such that, for a specific object, the runtime graph relates the specific object to another object that contains the specific object.
Satellite on-board processing for earth resources data
NASA Technical Reports Server (NTRS)
Bodenheimer, R. E.; Gonzalez, R. C.; Gupta, J. N.; Hwang, K.; Rochelle, R. W.; Wilson, J. B.; Wintz, P. A.
1975-01-01
Results of a survey of earth resources user applications and their data requirements, earth resources multispectral scanner sensor technology, and preprocessing algorithms for correcting the sensor outputs and for data bulk reduction are presented along with a candidate data format. Computational requirements required to implement the data analysis algorithms are included along with a review of computer architectures and organizations. Computer architectures capable of handling the algorithm computational requirements are suggested and the environmental effects of an on-board processor discussed. By relating performance parameters to the system requirements of each of the user requirements the feasibility of on-board processing is determined for each user. A tradeoff analysis is performed to determine the sensitivity of results to each of the system parameters. Significant results and conclusions are discussed, and recommendations are presented.
Optimizing Security of Cloud Computing within the DoD
2010-12-01
information security governance and risk management; application security; cryptography; security architecture and design; operations security; business ...governance and risk management; application security; cryptography; security architecture and design; operations security; business continuity...20 7. Operational Security (OPSEC).........................................................20 8. Business Continuity Planning (BCP) and Disaster
Study on Global GIS architecture and its key technologies
NASA Astrophysics Data System (ADS)
Cheng, Chengqi; Guan, Li; Lv, Xuefeng
2009-09-01
Global GIS (G2IS) is a system, which supports the huge data process and the global direct manipulation on global grid based on spheroid or ellipsoid surface. Based on global subdivision grid (GSG), Global GIS architecture is presented in this paper, taking advantage of computer cluster theory, the space-time integration technology and the virtual reality technology. Global GIS system architecture is composed of five layers, including data storage layer, data representation layer, network and cluster layer, data management layer and data application layer. Thereinto, it is designed that functions of four-level protocol framework and three-layer data management pattern of Global GIS based on organization, management and publication of spatial information in this architecture. Three kinds of core supportive technologies, which are computer cluster theory, the space-time integration technology and the virtual reality technology, and its application pattern in the Global GIS are introduced in detail. The primary ideas of Global GIS in this paper will be an important development tendency of GIS.
Study on Global GIS architecture and its key technologies
NASA Astrophysics Data System (ADS)
Cheng, Chengqi; Guan, Li; Lv, Xuefeng
2010-11-01
Global GIS (G2IS) is a system, which supports the huge data process and the global direct manipulation on global grid based on spheroid or ellipsoid surface. Based on global subdivision grid (GSG), Global GIS architecture is presented in this paper, taking advantage of computer cluster theory, the space-time integration technology and the virtual reality technology. Global GIS system architecture is composed of five layers, including data storage layer, data representation layer, network and cluster layer, data management layer and data application layer. Thereinto, it is designed that functions of four-level protocol framework and three-layer data management pattern of Global GIS based on organization, management and publication of spatial information in this architecture. Three kinds of core supportive technologies, which are computer cluster theory, the space-time integration technology and the virtual reality technology, and its application pattern in the Global GIS are introduced in detail. The primary ideas of Global GIS in this paper will be an important development tendency of GIS.
Platform Architecture for Decentralized Positioning Systems.
Kasmi, Zakaria; Norrdine, Abdelmoumen; Blankenbach, Jörg
2017-04-26
A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies) and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system.
Transportable GPU (General Processor Units) chip set technology for standard computer architectures
NASA Astrophysics Data System (ADS)
Fosdick, R. E.; Denison, H. C.
1982-11-01
The USAFR-developed GPU Chip Set has been utilized by Tracor to implement both USAF and Navy Standard 16-Bit Airborne Computer Architectures. Both configurations are currently being delivered into DOD full-scale development programs. Leadless Hermetic Chip Carrier packaging has facilitated implementation of both architectures on single 41/2 x 5 substrates. The CMOS and CMOS/SOS implementations of the GPU Chip Set have allowed both CPU implementations to use less than 3 watts of power each. Recent efforts by Tracor for USAF have included the definition of a next-generation GPU Chip Set that will retain the application-proven architecture of the current chip set while offering the added cost advantages of transportability across ISO-CMOS and CMOS/SOS processes and across numerous semiconductor manufacturers using a newly-defined set of common design rules. The Enhanced GPU Chip Set will increase speed by an approximate factor of 3 while significantly reducing chip counts and costs of standard CPU implementations.
Platform Architecture for Decentralized Positioning Systems
Kasmi, Zakaria; Norrdine, Abdelmoumen; Blankenbach, Jörg
2017-01-01
A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies) and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system. PMID:28445414
Performance study of a data flow architecture
NASA Technical Reports Server (NTRS)
Adams, George
1985-01-01
Teams of scientists studied data flow concepts, static data flow machine architecture, and the VAL language. Each team mapped its application onto the machine and coded it in VAL. The principal findings of the study were: (1) Five of the seven applications used the full power of the target machine. The galactic simulation and multigrid fluid flow teams found that a significantly smaller version of the machine (16 processing elements) would suffice. (2) A number of machine design parameters including processing element (PE) function unit numbers, array memory size and bandwidth, and routing network capability were found to be crucial for optimal machine performance. (3) The study participants readily acquired VAL programming skills. (4) Participants learned that application-based performance evaluation is a sound method of evaluating new computer architectures, even those that are not fully specified. During the course of the study, participants developed models for using computers to solve numerical problems and for evaluating new architectures. These models form the bases for future evaluation studies.
A Web Centric Architecture for Deploying Multi-Disciplinary Engineering Design Processes
NASA Technical Reports Server (NTRS)
Woyak, Scott; Kim, Hongman; Mullins, James; Sobieszczanski-Sobieski, Jaroslaw
2004-01-01
There are continuous needs for engineering organizations to improve their design process. Current state of the art techniques use computational simulations to predict design performance, and optimize it through advanced design methods. These tools have been used mostly by individual engineers. This paper presents an architecture for achieving results at an organization level beyond individual level. The next set of gains in process improvement will come from improving the effective use of computers and software within a whole organization, not just for an individual. The architecture takes advantage of state of the art capabilities to produce a Web based system to carry engineering design into the future. To illustrate deployment of the architecture, a case study for implementing advanced multidisciplinary design optimization processes such as Bi-Level Integrated System Synthesis is discussed. Another example for rolling-out a design process for Design for Six Sigma is also described. Each example explains how an organization can effectively infuse engineering practice with new design methods and retain the knowledge over time.
Persistent Memory in Single Node Delay-Coupled Reservoir Computing.
Kovac, André David; Koall, Maximilian; Pipa, Gordon; Toutounji, Hazem
2016-01-01
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality.
Persistent Memory in Single Node Delay-Coupled Reservoir Computing
Pipa, Gordon; Toutounji, Hazem
2016-01-01
Delays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality. PMID:27783690
ERIC Educational Resources Information Center
Huston, Rick, Ed.; Armel, Donald, Ed.
Topics addressed by 40 papers from a conference on microcomputers include: developing a campus wide computer ethics policy; integrating new technologies into professional education; campus computer networks; computer assisted instruction; client/server architecture; competencies for entry-level computing positions; auditing and professional…
NASA Technical Reports Server (NTRS)
1972-01-01
The design is reported of an advanced modular computer system designated the Automatically Reconfigurable Modular Multiprocessor System, which anticipates requirements for higher computing capacity and reliability for future spaceborne computers. Subjects discussed include: an overview of the architecture, mission analysis, synchronous and nonsynchronous scheduling control, reliability, and data transmission.
NASA Technical Reports Server (NTRS)
1989-01-01
The results of the refined conceptual design phase (task 5) of the Simulation Computer System (SCS) study are reported. The SCS is the computational portion of the Payload Training Complex (PTC) providing simulation based training on payload operations of the Space Station Freedom (SSF). In task 4 of the SCS study, the range of architectures suitable for the SCS was explored. Identified system architectures, along with their relative advantages and disadvantages for SCS, were presented in the Conceptual Design Report. Six integrated designs-combining the most promising features from the architectural formulations-were additionally identified in the report. The six integrated designs were evaluated further to distinguish the more viable designs to be refined as conceptual designs. The three designs that were selected represent distinct approaches to achieving a capable and cost effective SCS configuration for the PTC. Here, the results of task 4 (input to this task) are briefly reviewed. Then, prior to describing individual conceptual designs, the PTC facility configuration and the SSF systems architecture that must be supported by the SCS are reviewed. Next, basic features of SCS implementation that have been incorporated into all selected SCS designs are considered. The details of the individual SCS designs are then presented before making a final comparison of the three designs.
High End Computing Technologies for Earth Science Applications: Trends, Challenges, and Innovations
NASA Technical Reports Server (NTRS)
Parks, John (Technical Monitor); Biswas, Rupak; Yan, Jerry C.; Brooks, Walter F.; Sterling, Thomas L.
2003-01-01
Earth science applications of the future will stress the capabilities of even the highest performance supercomputers in the areas of raw compute power, mass storage management, and software environments. These NASA mission critical problems demand usable multi-petaflops and exabyte-scale systems to fully realize their science goals. With an exciting vision of the technologies needed, NASA has established a comprehensive program of advanced research in computer architecture, software tools, and device technology to ensure that, in partnership with US industry, it can meet these demanding requirements with reliable, cost effective, and usable ultra-scale systems. NASA will exploit, explore, and influence emerging high end computing architectures and technologies to accelerate the next generation of engineering, operations, and discovery processes for NASA Enterprises. This article captures this vision and describes the concepts, accomplishments, and the potential payoff of the key thrusts that will help meet the computational challenges in Earth science applications.
Deep learning with coherent nanophotonic circuits
NASA Astrophysics Data System (ADS)
Shen, Yichen; Harris, Nicholas C.; Skirlo, Scott; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Sun, Xin; Zhao, Shijie; Larochelle, Hugo; Englund, Dirk; Soljačić, Marin
2017-07-01
Artificial neural networks are computational network models inspired by signal processing in the brain. These models have dramatically improved performance for many machine-learning tasks, including speech and image recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made towards developing electronic architectures tuned to implement artificial neural networks that exhibit improved computational speed and accuracy. Here, we propose a new architecture for a fully optical neural network that, in principle, could offer an enhancement in computational speed and power efficiency over state-of-the-art electronics for conventional inference tasks. We experimentally demonstrate the essential part of the concept using a programmable nanophotonic processor featuring a cascaded array of 56 programmable Mach-Zehnder interferometers in a silicon photonic integrated circuit and show its utility for vowel recognition.
Production experience with the ATLAS Event Service
NASA Astrophysics Data System (ADS)
Benjamin, D.; Calafiura, P.; Childers, T.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.; ATLAS Collaboration
2017-10-01
The ATLAS Event Service (AES) has been designed and implemented for efficient running of ATLAS production workflows on a variety of computing platforms, ranging from conventional Grid sites to opportunistic, often short-lived resources, such as spot market commercial clouds, supercomputers and volunteer computing. The Event Service architecture allows real time delivery of fine grained workloads to running payload applications which process dispatched events or event ranges and immediately stream the outputs to highly scalable Object Stores. Thanks to its agile and flexible architecture the AES is currently being used by grid sites for assigning low priority workloads to otherwise idle computing resources; similarly harvesting HPC resources in an efficient back-fill mode; and massively scaling out to the 50-100k concurrent core level on the Amazon spot market to efficiently utilize those transient resources for peak production needs. Platform ports in development include ATLAS@Home (BOINC) and the Google Compute Engine, and a growing number of HPC platforms. After briefly reviewing the concept and the architecture of the Event Service, we will report the status and experience gained in AES commissioning and production operations on supercomputers, and our plans for extending ES application beyond Geant4 simulation to other workflows, such as reconstruction and data analysis.
The computational structural mechanics testbed architecture. Volume 2: The interface
NASA Technical Reports Server (NTRS)
Felippa, Carlos A.
1988-01-01
This is the third set of five volumes which describe the software architecture for the Computational Structural Mechanics Testbed. Derived from NICE, an integrated software system developed at Lockheed Palo Alto Research Laboratory, the architecture is composed of the command language CLAMP, the command language interpreter CLIP, and the data manager GAL. Volumes 1, 2, and 3 (NASA CR's 178384, 178385, and 178386, respectively) describe CLAMP and CLIP and the CLIP-processor interface. Volumes 4 and 5 (NASA CR's 178387 and 178388, respectively) describe GAL and its low-level I/O. CLAMP, an acronym for Command Language for Applied Mechanics Processors, is designed to control the flow of execution of processors written for NICE. Volume 3 describes the CLIP-Processor interface and related topics. It is intended only for processor developers.
Integrated command, control, communications and computation system functional architecture
NASA Technical Reports Server (NTRS)
Cooley, C. G.; Gilbert, L. E.
1981-01-01
The functional architecture for an integrated command, control, communications, and computation system applicable to the command and control portion of the NASA End-to-End Data. System is described including the downlink data processing and analysis functions required to support the uplink processes. The functional architecture is composed of four elements: (1) the functional hierarchy which provides the decomposition and allocation of the command and control functions to the system elements; (2) the key system features which summarize the major system capabilities; (3) the operational activity threads which illustrate the interrelationahip between the system elements; and (4) the interfaces which illustrate those elements that originate or generate data and those elements that use the data. The interfaces also provide a description of the data and the data utilization and access techniques.
The computational structural mechanics testbed architecture. Volume 1: The language
NASA Technical Reports Server (NTRS)
Felippa, Carlos A.
1988-01-01
This is the first set of five volumes which describe the software architecture for the Computational Structural Mechanics Testbed. Derived from NICE, an integrated software system developed at Lockheed Palo Alto Research Laboratory, the architecture is composed of the command language CLAMP, the command language interpreter CLIP, and the data manager GAL. Volumes 1, 2, and 3 (NASA CR's 178384, 178385, and 178386, respectively) describe CLAMP and CLIP, and the CLIP-processor interface. Volumes 4 and 5 (NASA CR's 178387 and 178388, respectively) describe GAL and its low-level I/O. CLAMP, an acronym for Command Language for Applied Mechanics Processors, is designed to control the flow of execution of processors written for NICE. Volume 1 presents the basic elements of the CLAMP language and is intended for all users.
The computation in diagnostics for tokamaks: systems, designs, approaches
NASA Astrophysics Data System (ADS)
Krawczyk, Rafał; Linczuk, Paweł; Czarski, Tomasz; Wojeński, Andrzej; Chernyshova, Maryna; Poźniak, Krzysztof; Kolasiński, Piotr; Kasprowicz, Grzegorz; Zabołotny, Wojciech; Kowalska-Strzeciwilk, Ewa; Malinowski, Karol; Gaska, Michał
2017-08-01
The requirements given for GEM (Gaseous Electron Multiplier) detector based acquisition system for plasma impurities diagnostics triggered a need for the development of a specialized software and hardware architecture. The amount of computations with latency and throughput restrictions cause that an advanced solution is sought for. In order to provide a mechanism fitting the designated tokamaks, an insight into existing solutions was necessary. In the article there is discussed architecture of systems used for plasma diagnostics and in related scientific fields. The developed solution is compared and contrasted with other diagnostic and control systems. Particular attention is payed to specific requirements for plasma impurities diagnostics in tokamak thermal fusion reactor. Subsequently, the details are presented that justified the choice of the system architecture and the discussion on various approaches is given.
The computational structural mechanics testbed architecture. Volume 2: Directives
NASA Technical Reports Server (NTRS)
Felippa, Carlos A.
1989-01-01
This is the second of a set of five volumes which describe the software architecture for the Computational Structural Mechanics Testbed. Derived from NICE, an integrated software system developed at Lockheed Palo Alto Research Laboratory, the architecture is composed of the command language (CLAMP), the command language interpreter (CLIP), and the data manager (GAL). Volumes 1, 2, and 3 (NASA CR's 178384, 178385, and 178386, respectively) describe CLAMP and CLIP and the CLIP-processor interface. Volumes 4 and 5 (NASA CR's 178387 and 178388, respectively) describe GAL and its low-level I/O. CLAMP, an acronym for Command Language for Applied Mechanics Processors, is designed to control the flow of execution of processors written for NICE. Volume 2 describes the CLIP directives in detail. It is intended for intermediate and advanced users.
1994-05-01
PARALLEL DISTRIBUTED MEMORY ARCHITECTURE LTJh T. M. Eidson 0 - 8 l 9 5 " G. Erlebacher _ _ _. _ DTIe QUALITY INSPECTED a Contract NAS I - 19480 May 1994...DISTRIBUTED MEMORY ARCHITECTURE T.M. Eidson * High Technology Corporation Hampton, VA 23665 G. Erlebachert Institute for Computer Applications in Science and...developed and evaluated. Simple model calculations as well as timing results are pres.nted to evaluate the various strategies. The particular
Overview of the LINCS architecture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fletcher, J.G.; Watson, R.W.
1982-01-13
Computing at the Lawrence Livermore National Laboratory (LLNL) has evolved over the past 15 years with a computer network based resource sharing environment. The increasing use of low cost and high performance micro, mini and midi computers and commercially available local networking systems will accelerate this trend. Further, even the large scale computer systems, on which much of the LLNL scientific computing depends, are evolving into multiprocessor systems. It is our belief that the most cost effective use of this environment will depend on the development of application systems structured into cooperating concurrent program modules (processes) distributed appropriately over differentmore » nodes of the environment. A node is defined as one or more processors with a local (shared) high speed memory. Given the latter view, the environment can be characterized as consisting of: multiple nodes communicating over noisy channels with arbitrary delays and throughput, heterogenous base resources and information encodings, no single administration controlling all resources, distributed system state, and no uniform time base. The system design problem is - how to turn the heterogeneous base hardware/firmware/software resources of this environment into a coherent set of resources that facilitate development of cost effective, reliable, and human engineered applications. We believe the answer lies in developing a layered, communication oriented distributed system architecture; layered and modular to support ease of understanding, reconfiguration, extensibility, and hiding of implementation or nonessential local details; communication oriented because that is a central feature of the environment. The Livermore Interactive Network Communication System (LINCS) is a hierarchical architecture designed to meet the above needs. While having characteristics in common with other architectures, it differs in several respects.« less
Cloud Computing in Support of Synchronized Disaster Response Operations
2010-09-01
scalable, Web application based on cloud computing technologies to facilitate communication between a broad range of public and private entities without...requiring them to compromise security or competitive advantage. The proposed design applies the unique benefits of cloud computing architectures such as
Why is a computational framework for motivational and metacognitive control needed?
NASA Astrophysics Data System (ADS)
Sun, Ron
2018-01-01
This paper discusses, in the context of computational modelling and simulation of cognition, the relevance of deeper structures in the control of behaviour. Such deeper structures include motivational control of behaviour, which provides underlying causes for actions, and also metacognitive control, which provides higher-order processes for monitoring and regulation. It is argued that such deeper structures are important and thus cannot be ignored in computational cognitive architectures. A general framework based on the Clarion cognitive architecture is outlined that emphasises the interaction amongst action selection, motivation, and metacognition. The upshot is that it is necessary to incorporate all essential processes; short of that, the understanding of cognition can only be incomplete.
EOS MLS Science Data Processing System: A Description of Architecture and Capabilities
NASA Technical Reports Server (NTRS)
Cuddy, David T.; Echeverri, Mark D.; Wagner, Paul A.; Hanzel, Audrey T.; Fuller, Ryan A.
2006-01-01
This paper describes the architecture and capabilities of the Science Data Processing System (SDPS) for the EOS MLS. The SDPS consists of two major components--the Science Computing Facility and the Science Investigator-led Processing System. The Science Computing Facility provides the facilities for the EOS MLS Science Team to perform the functions of scientific algorithm development, processing software development, quality control of data products, and scientific analyses. The Science Investigator-led Processing System processes and reprocesses the science data for the entire mission and delivers the data products to the Science Computing Facility and to the Goddard Space Flight Center Earth Science Distributed Active Archive Center, which archives and distributes the standard science products.
Super-resolution using a light inception layer in convolutional neural network
NASA Astrophysics Data System (ADS)
Mou, Qinyang; Guo, Jun
2018-04-01
Recently, several models based on CNN architecture have achieved great result on Single Image Super-Resolution (SISR) problem. In this paper, we propose an image super-resolution method (SR) using a light inception layer in convolutional network (LICN). Due to the strong representation ability of our well-designed inception layer that can learn richer representation with less parameters, we can build our model with shallow architecture that can reduce the effect of vanishing gradients problem and save computational costs. Our model strike a balance between computational speed and the quality of the result. Compared with state-of-the-art result, we produce comparable or better results with faster computational speed.
Access control and privacy in large distributed systems
NASA Technical Reports Server (NTRS)
Leiner, B. M.; Bishop, M.
1986-01-01
Large scale distributed systems consists of workstations, mainframe computers, supercomputers and other types of servers, all connected by a computer network. These systems are being used in a variety of applications including the support of collaborative scientific research. In such an environment, issues of access control and privacy arise. Access control is required for several reasons, including the protection of sensitive resources and cost control. Privacy is also required for similar reasons, including the protection of a researcher's proprietary results. A possible architecture for integrating available computer and communications security technologies into a system that meet these requirements is described. This architecture is meant as a starting point for discussion, rather that the final answer.
Open architecture CMM motion controller
NASA Astrophysics Data System (ADS)
Chang, David; Spence, Allan D.; Bigg, Steve; Heslip, Joe; Peterson, John
2001-12-01
Although initially the only Coordinate Measuring Machine (CMM) sensor available was a touch trigger probe, technological advances in sensors and computing have greatly increased the variety of available inspection sensors. Non-contact laser digitizers and analog scanning touch probes require very well tuned CMM motion control, as well as an extensible, open architecture interface. This paper describes the implementation of a retrofit CMM motion controller designed for open architecture interface to a variety of sensors. The controller is based on an Intel Pentium microcomputer and a Servo To Go motion interface electronics card. Motor amplifiers, safety, and additional interface electronics are housed in a separate enclosure. Host Signal Processing (HSP) is used for the motion control algorithm. Compared to the usual host plus DSP architecture, single CPU HSP simplifies integration with the various sensors, and implementation of software geometric error compensation. Motion control tuning is accomplished using a remote computer via 100BaseTX Ethernet. A Graphical User Interface (GUI) is used to enter geometric error compensation data, and to optimize the motion control tuning parameters. It is shown that this architecture achieves the required real time motion control response, yet is much easier to extend to additional sensors.
Bioinspired architecture approach for a one-billion transistor smart CMOS camera chip
NASA Astrophysics Data System (ADS)
Fey, Dietmar; Komann, Marcus
2007-05-01
In the paper we present a massively parallel VLSI architecture for future smart CMOS camera chips with up to one billion transistors. To exploit efficiently the potential offered by future micro- or nanoelectronic devices traditional on central structures oriented parallel architectures based on MIMD or SIMD approaches will fail. They require too long and too many global interconnects for the distribution of code or the access to common memory. On the other hand nature developed self-organising and emergent principles to manage successfully complex structures based on lots of interacting simple elements. Therefore we developed a new as Marching Pixels denoted emergent computing paradigm based on a mixture of bio-inspired computing models like cellular automaton and artificial ants. In the paper we present different Marching Pixels algorithms and the corresponding VLSI array architecture. A detailed synthesis result for a 0.18 μm CMOS process shows that a 256×256 pixel image is processed in less than 10 ms assuming a moderate 100 MHz clock rate for the processor array. Future higher integration densities and a 3D chip stacking technology will allow the integration and processing of Mega pixels within the same time since our architecture is fully scalable.
Remote hardware-reconfigurable robotic camera
NASA Astrophysics Data System (ADS)
Arias-Estrada, Miguel; Torres-Huitzil, Cesar; Maya-Rueda, Selene E.
2001-10-01
In this work, a camera with integrated image processing capabilities is discussed. The camera is based on an imager coupled to an FPGA device (Field Programmable Gate Array) which contains an architecture for real-time computer vision low-level processing. The architecture can be reprogrammed remotely for application specific purposes. The system is intended for rapid modification and adaptation for inspection and recognition applications, with the flexibility of hardware and software reprogrammability. FPGA reconfiguration allows the same ease of upgrade in hardware as a software upgrade process. The camera is composed of a digital imager coupled to an FPGA device, two memory banks, and a microcontroller. The microcontroller is used for communication tasks and FPGA programming. The system implements a software architecture to handle multiple FPGA architectures in the device, and the possibility to download a software/hardware object from the host computer into its internal context memory. System advantages are: small size, low power consumption, and a library of hardware/software functionalities that can be exchanged during run time. The system has been validated with an edge detection and a motion processing architecture, which will be presented in the paper. Applications targeted are in robotics, mobile robotics, and vision based quality control.
Hybrid architecture for building secure sensor networks
NASA Astrophysics Data System (ADS)
Owens, Ken R., Jr.; Watkins, Steve E.
2012-04-01
Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.
Information Interaction: Providing a Framework for Information Architecture.
ERIC Educational Resources Information Center
Toms, Elaine G.
2002-01-01
Discussion of information architecture focuses on a model of information interaction that bridges the gap between human and computer and between information behavior and information retrieval. Illustrates how the process of information interaction is affected by the user, the system, and the content. (Contains 93 references.) (LRW)
Federal Register 2010, 2011, 2012, 2013, 2014
2013-12-12
... design feature associated with the architecture and connectivity capabilities of the airplanes' computer... the comment for an association, business, labor union, etc.). DOT's complete Privacy Act Statement can...; facsimile 425-227-1149. SUPPLEMENTARY INFORMATION: The proposed network architecture includes the following...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-12-10
... design feature associated with the architecture and connectivity capabilities of the airplanes' computer... vulnerabilities to the airplanes' systems. The proposed network architecture includes the following connectivity.... Operator business and administrative support systems, and 3. Passenger entertainment systems, and access by...
Guidance and Control System for an Autonomous Vehicle
1990-06-01
implementing an appropriate computer architecture in support of these goals is also discussed and detailed, along with the choice of associated computer hardware and real - time operating system software. (rh)
Qubit Architecture with High Coherence and Fast Tunable Coupling.
Chen, Yu; Neill, C; Roushan, P; Leung, N; Fang, M; Barends, R; Kelly, J; Campbell, B; Chen, Z; Chiaro, B; Dunsworth, A; Jeffrey, E; Megrant, A; Mutus, J Y; O'Malley, P J J; Quintana, C M; Sank, D; Vainsencher, A; Wenner, J; White, T C; Geller, Michael R; Cleland, A N; Martinis, John M
2014-11-28
We introduce a superconducting qubit architecture that combines high-coherence qubits and tunable qubit-qubit coupling. With the ability to set the coupling to zero, we demonstrate that this architecture is protected from the frequency crowding problems that arise from fixed coupling. More importantly, the coupling can be tuned dynamically with nanosecond resolution, making this architecture a versatile platform with applications ranging from quantum logic gates to quantum simulation. We illustrate the advantages of dynamical coupling by implementing a novel adiabatic controlled-z gate, with a speed approaching that of single-qubit gates. Integrating coherence and scalable control, the introduced qubit architecture provides a promising path towards large-scale quantum computation and simulation.
Pape-Haugaard, Louise; Frank, Lars
2011-01-01
A major obstacle in ensuring ubiquitous information is the utilization of heterogeneous systems in eHealth. The objective in this paper is to illustrate how an architecture for distributed eHealth databases can be designed without lacking the characteristic features of traditional sustainable databases. The approach is firstly to explain traditional architecture in central and homogeneous distributed database computing, followed by a possible approach to use an architectural framework to obtain sustainability across disparate systems i.e. heterogeneous databases, concluded with a discussion. It is seen that through a method of using relaxed ACID properties on a service-oriented architecture it is possible to achieve data consistency which is essential when ensuring sustainable interoperability.
Fourier transform spectrometer controller for partitioned architectures
NASA Astrophysics Data System (ADS)
Tamas-Selicean, D.; Keymeulen, D.; Berisford, D.; Carlson, R.; Hand, K.; Pop, P.; Wadsworth, W.; Levy, R.
The current trend in spacecraft computing is to integrate applications of different criticality levels on the same platform using no separation. This approach increases the complexity of the development, verification and integration processes, with an impact on the whole system life cycle. Researchers at ESA and NASA advocated for the use of partitioned architecture to reduce this complexity. Partitioned architectures rely on platform mechanisms to provide robust temporal and spatial separation between applications. Such architectures have been successfully implemented in several industries, such as avionics and automotive. In this paper we investigate the challenges of developing and the benefits of integrating a scientific instrument, namely a Fourier Transform Spectrometer, in such a partitioned architecture.
A survey of compiler optimization techniques
NASA Technical Reports Server (NTRS)
Schneck, P. B.
1972-01-01
Major optimization techniques of compilers are described and grouped into three categories: machine dependent, architecture dependent, and architecture independent. Machine-dependent optimizations tend to be local and are performed upon short spans of generated code by using particular properties of an instruction set to reduce the time or space required by a program. Architecture-dependent optimizations are global and are performed while generating code. These optimizations consider the structure of a computer, but not its detailed instruction set. Architecture independent optimizations are also global but are based on analysis of the program flow graph and the dependencies among statements of source program. A conceptual review of a universal optimizer that performs architecture-independent optimizations at source-code level is also presented.