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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Open solutions to distributed control in ground tracking stations

The advent of high speed local area networks has made it possible to interconnect small, powerful computers to function together as a single large computer. Today, distributed computer systems are the new paradigm for large scale computing systems. However, the communications provided by the local area network is only one part of the solution. The services and protocols used by the application programs to communicate across the network are as indispensable as the local area network. And the selection of services and protocols that do not match the system requirements will limit the capabilities, performance, and expansion of the system. Proprietary solutions are available but are usually limited to a select set of equipment. However, there are two solutions based on 'open' standards. The question that must be answered is 'which one is the best one for my job?' This paper examines a model for tracking stations and their requirements for interprocessor communications in the next century. The model and requirements are matched with the model and services provided by the five different software architectures and supporting protocol solutions. Several key services are examined in detail to determine which services and protocols most closely match the requirements for the tracking station environment. The study reveals that the protocols are tailored to the problem domains for which they were originally designed. Further, the study reveals that the process control model is the closest match to the tracking station model.

Heuser, William Randy↗
NASA NTRS1989

Ordered fast fourier transforms on a massively parallel hypercube multiprocessor

Design alternatives for ordered Fast Fourier Transformation (FFT) algorithms were examined on massively parallel hypercube multiprocessors such as the Connection Machine. Particular emphasis is placed on reducing communication which is known to dominate the overall computing time. To this end, the order and computational phases of the FFT were combined, and the sequence to processor maps that reduce communication were used. The class of ordered transforms is expanded to include any FFT in which the order of the transform is the same as that of the input sequence. Two such orderings are examined, namely, standard-order and A-order which can be implemented with equal ease on the Connection Machine where orderings are determined by geometries and priorities. If the sequence has N = 2 exp r elements and the hypercube has P = 2 exp d processors, then a standard-order FFT can be implemented with d + r/2 + 1 parallel transmissions. An A-order sequence can be transformed with 2d - r/2 parallel transmissions which is r - d + 1 fewer than the standard order. A parallel method for computing the trigonometric coefficients is presented that does not use trigonometric functions or interprocessor communication. A performance of 0.9 GFLOPS was obtained for an A-order transform on the Connection Machine.

Tong, Charles↗
DOE OSTI2017

MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A≈WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient parallel algorithms to solve the problem for big data sets. The main contribution of this work is a new, high-performance parallel computational framework for a broad class of NMF algorithms that iteratively solves alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). The framework is flexible and able to leverage a variety of NMF and NLS algorithms, including Multiplicative Update, Hierarchical Alternating Least Squares, and Block Principal Pivoting. Our implementation allows us to benchmark and compare different algorithms on massive dense and sparse data matrices of size that spans from few hundreds of millions to billions. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements. The code and the datasets used for conducting the experiments are available online.

2D↗
DOE OSTI2016

A high-performance parallel algorithm for nonnegative matrix factorization

Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A ≈ WH. NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for W and H. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementations, our algorithm is also flexible: (1) it performs well for both dense and sparse matrices, and (2) it allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors W and H within the alternating iterations. We demonstrate the scalability of our algorithm and compare it with baseline implementations, showing significant performance improvements.

Kannan, Ramakrishnan↗
DOE OSTI2018

A 3D Parallel Algorithm for QR Decomposition

Interprocessor communication often dominates the runtime of large matrix computations. Here, we present a parallel algorithm for computing QR decompositions whose bandwidth cost (communication volume) can be decreased at the cost of increasing its latency cost (number of messages). By varying a parameter to navigate the bandwidth/latency tradeoff, we can tune this algorithm for machines with different communication costs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

HPC-NMF: A High-Performance Parallel Algorithm for Nonnegative Matrix Factorization

NMF is a useful tool for many applications in different domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of efficient distributed algorithms to solve the problem for big data sets. We propose a high-performance distributed-memory parallel algorithm that computes the factorization by iteratively solving alternating non-negative least squares (NLS) subproblems for $\WW$ and $\HH$. It maintains the data and factor matrices in memory (distributed across processors), uses MPI for interprocessor communication, and, in the dense case, provably minimizes communication costs (under mild assumptions). As opposed to previous implementation, our algorithm is also flexible: It performs well for both dense and sparse matrices, and allows the user to choose any one of the multiple algorithms for solving the updates to low rank factors $\WW$ and $\HH$ within the alternating iterations.

Kannan, Ramakrishnan↗
DOE OSTI2018

Institute for Sustained Performance, Energy, and Resilience (SUPER): University of Utah Final Report

Over the course of this project, computational scientists working on behalf of the Department of Energy's Office of Science (DOE SC) were exploiting a new generation of petascale computing resources to make previously inaccessible discoveries in a broad range of disciplines including physics, chemistry and material science. The computational systems underpinning this work increased in performance potential from tens to hundreds of Pflop/s, and evolved significantly from those in use at the beginning of the project in terms of available concurrency; wider use of accelerators such as graphics processing units(GPUs); and changes to the memory hierarchy including the incorporation of a new generation of persistent devices (e.g., phase change memory). To ensure that DOE's computational scientists can successfully exploit this emerging generation of high performance computing (HPC) systems, the University of Southern California (USC) assembled a broad team of computer scientists with the expertise to address the most pressing challenges of DOE's computing systems: (a) end-to-end performance optimization, including single-node performance, interprocessor communication, load balancing and I/O; (b) performance portability for heterogeneous systems, including accelerators; (c) minimizing energy consumption; (d) resilient computation; and, (e) exploiting new memory technology.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

A multi-microprocessor system for finite element structural analysis

During the last few years, advances in microprocessor technology have spurred a renewed interest in special-purpose computers. The microprocessor has become small, inexpensive, and powerful enough to be considered as a building block for special-purpose hardware. A description is presented of the architecture of a prototype 'finite element machine' currently being built. Attention is given to details regarding the finite element analysis problem, the arrangement of the processors as finite element nodes in the structural model, the influence of the architecture on the solution algorithm, interprocessor communication primitives, and the performance of the finite element machine.

Jordan, H. F.↗
NASA NTRS1982

Application of integration algorithms in a parallel processing environment for the simulation of jet engines

The application of Predictor corrector integration algorithms developed for the digital parallel processing environment are investigated. The algorithms are implemented and evaluated through the use of a software simulator which provides an approximate representation of the parallel processing hardware. Test cases which focus on the use of the algorithms are presented and a specific application using a linear model of a turbofan engine is considered. Results are presented showing the effects of integration step size and the number of processors on simulation accuracy. Real time performance, interprocessor communication, and algorithm startup are also discussed.

Krosel, S. M.↗
NASA NTRS1984

A unified data flow model for fault tolerant computers

The Dataflow Simulation System (DFSS) at USL was used as the medium on which a functional simulaton of sIFT was produced. DFSS is written in PL/I and is supported by MULTICS. Within the simulation, all the interprocessor communication, fault simulation, system state data, and monitoring were implemented in dataflow and supported directly by DFSS. The actual processor level computation was carried out by the SIFT code in PASCAL. The interface between DFSS in PL/I and the SIFT code in PASCAL was supported under a mechanism in DFSS called a Node Realization Module (NRM).

Rao, T. R.↗
NASA NTRS1983

Multibus-based parallel processor for simulation

A Multibus-based parallel processor simulation system is described. The system is intended to serve as a vehicle for gaining hands-on experience, testing system and application software, and evaluating parallel processor performance during development of a larger system based on the horizontal/vertical-bus interprocessor communication mechanism. The prototype system consists of up to seven Intel iSBC 86/12A single-board computers which serve as processing elements, a multiple transmission controller (MTC) designed to support system operation, and an Intel Model 225 Microcomputer Development System which serves as the user interface and input/output processor. All components are interconnected by a Multibus/IEEE 796 bus. An important characteristic of the system is that it provides a mechanism for a processing element to broadcast data to other selected processing elements. This parallel transfer capability is provided through the design of the MTC and a minor modification to the iSBC 86/12A board. The operation of the MTC, the basic hardware-level operation of the system, and pertinent details about the iSBC 86/12A and the Multibus are described.

Ogrady, E. P.↗
NASA NTRS1986

Stencils and problem partitionings: Their influence on the performance of multiple processor systems

Given a discretization stencil, partitioning the problem domain is an important first step for the efficient solution of partial differential equations on multiple processor systems. Partitions are derived that minimize interprocessor communication when the number of processors is known a priori and each domain partition is assigned to a different processor. This partitioning technique uses the stencil structure to select appropriate partition shapes. For square problem domains, it is shown that non-standard partitions (e.g., hexagons) are frequently preferable to the standard square partitions for a variety of commonly used stencils. This investigation is concluded with a formalization of the relationship between partition shape, stencil structure, and architecture, allowing selection of optimal partitions for a variety of parallel systems.

Reed, D. A.↗
NASA NTRS1987

Stencils and problem partitionings - Their influence on the performance of multiple processor systems

Given a discretization stencil, partitioning the problem domain is an important first step for the efficient solution of partial differential equations on multiple processor systems. Partitions are derived that minimize interprocessor communication when the number of processors is known a priori and each domain partition is assigned to a different processor. This partitioning technique uses the stencil structure to select appropriate partition shapes. For square problem domains, it is shown that non-standard partitions (e.g., hexagons) are frequently preferable to the standard square partitions for a variety of commonly used stencils. This investigation is concluded with a formalization of the relationship between partition shape, stencil structure, and architecture, allowing selection of optimal partitions for a variety of parallel systems.

Reed, Daniel A.↗
NASA NTRS1987

Performance limitations in parallel processor simulations

A jet-engine model is partitioned and simulated on a parallel processor system consisting of five 8086/8087 floating-point computers. The simulation uses Heun's integration method. A near-optimal parallel simulation (in the sense of minimum execution time) achieves speedup of only 2.13 and efficiency of 42.6 percent, in effect wasting 57.4 percent of the available processing power. A detailed analysis identifies and graphically demonstrates why the system fails to achieve ideal performance (viz., speedup of 5 and efficiency of 100 percent). Inherent characteristics of the problem equations and solution algorithm account for the loss of nearly half of the available processing power. Overheads associated with interprocessor communication and processor synchronization account for only a small fraction of the lost processing power. The effects of these and other factors which limit parallel processor performance are illustrated through real-time timing-analyzer tracers describing the run/idle status of the parallel processors during the simulation.

O'Grady, E. Pearse↗
NASA NTRS1987

A hierarchically distributed architecture for fault isolation expert systems on the space station

The Space Station Axiomatic Fault Isolating Expert Systems (SAFTIES) system deals with the hierarchical distribution of control and knowledge among independent expert systems doing fault isolation and scheduling of Space Station subsystems. On its lower level, fault isolation is performed on individual subsystems. These fault isolation expert systems contain knowledge about the performance requirements of their particular subsystem and corrective procedures which may be involved in repsonse to certain performance errors. They can control the functions of equipment in their system and coordinate system task schedules. On a higher level, the Executive contains knowledge of all resources, task schedules for all systems, and the relative priority of all resources and tasks. The executive can override any subsystem task schedule in order to resolve use conflicts or resolve errors that require resources from multiple subsystems. Interprocessor communication is implemented using the SAFTIES Communications Interface (SCI). The SCI is an application layer protocol which supports the SAFTIES distributed multi-level architecture.

Miksell, Steve↗
NASA NTRS1989

Concurrent algorithms for transient FE analysis

Information on concurrent algorithms for transient finite element analysis is given in viewgraph form. Information is given on concurrent dynamic algorithms, interprocessor communication, the performance of the BAR problem on the 32 Processor Hypercube, computational efficiency and accuracy analysis.

Ortiz, M.↗
NASA NTRS1989

Efficiency of group implicit concurrent algorithms for transient finite element analysis

The performance of group implicit algorithms is assessed on actual concurrent computers. It is shown that, as the number of subdomains is increased, performance enhancements are derived from two sources: the increased parallelism in the computations; and a reduction in equation solving effort. Moreover, these two performance enhancements are synergistic, in the sense that the corresponding speed-ups are multiplied, rather than merely added. Simulations on a 32-node hypercube are presented for which the interprocessor communications efficiencies obtained are consistently in excess of 90 percent.

Ortiz, M.↗