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Efficient parallel processing used to implement complex decoders. Hypercube multiprocessor connection scheme practical to decode long convolutional codes with efficient use of hardware. Hypercube design reduces both communication time among processors and space needed for interconnection. Decoding concept applicable to concurrent processing of digital signals using convolutional codes for error correction.
The Fault Tolerant Multiprocessor (FTMP) computer system was constructed using the Rockwell/Collins CAPS-6 processor. It is installed in the Avionics Integration Research Laboratory (AIRLAB) of NASA Langley Research Center. It is hosted by AIRLAB's System 10, a VAX 11/750, for the loading of programs and experimentation. The FTMP support software includes a cross compiler for a high level language called Automated Engineering Design (AED) System, an assembler for the CAPS-6 processor assembly language, and a linker. Access to this support software is through an automated remote access facility on the VAX which relieves the user of the burden of learning how to use the IBM 4381. This manual is a compilation of information about the FTMP support environment. It explains the FTMP software and support environment along many of the finer points of running programs on FTMP. This will be helpful to the researcher trying to run an experiment on FTMP and even to the person probing FTMP with fault injections. Much of the information in this manual can be found in other sources; we are only attempting to bring together the basic points in a single source. If the reader should need points clarified, there is a list of support documentation in the back of this manual.
In this paper, we analyze and compare the performance on a hypercube multiprocessor of some of the major multigrid techniques used in practice. The model problem considered here is that of solving the 2-D incompressible Navier-Stokes equations representing the flow between two parallel plates. Results obtained by implementing the different multigrid schemes on an iPSC are presented. Effects on the overall performance of various parameters of the algorithms, of the partitioning strategies employed, and of some of the characteristics of the underlying architecture are discussed.
Presented are schemes for implementing multigrid algorithms on message based MIMD multiprocessor systems. To address the various issues involved, a nontrivial problem of solving the 2-D incompressible Navier-Stokes equations is considered as the model problem. Three different multigrid algorithms are considered. Results from implementing these algorithms on an Intel iPSC are presented.
The design, implementation, and performance evaluation of a message passing facility (MPF) for shared memory multiprocessors are presented. The MPF is based on a message passing model conceptually similar to conversations. Participants (parallel processors) can enter or leave a conversation at any time. The message passing primitives for this model are implemented as a portable library of C function calls. The MPF is currently operational on a Sequent Balance 21000, and several parallel applications were developed and tested. Several simple benchmark programs are presented to establish interprocess communication performance for common patterns of interprocess communication. Finally, performance figures are presented for two parallel applications, linear systems solution, and iterative solution of partial differential equations.
The development and evaluation of fault-tolerant computer architectures and software-implemented fault tolerance (SIFT) for use in advanced NASA vehicles and potentially in flight-control systems are described in a collection of previously published reports prepared for NASA. Topics addressed include the principles of fault-tolerant multiprocessor (FTMP) operation; processor and slave regional designs; FTMP executive, facilities, acceptance-test/diagnostic, applications, and support software; FTM reliability and availability models; SIFT hardware design; and SIFT validation and verification.
This paper describes the application of a portion of a validation methodology to NASA's Fault-Tolerant Multiprocessor System (FTMP) and the Software Implemented Fault-Tolerance (SIFT) computer system. The methodology entails a building block approach, starting with simple baseline experiments and building to more complex experiments. The goal of the validation methodology is to thoroughly test and characterize the performance and behavior of ultrareliable computer systems. The validation methodology presented in this paper showed that the methodology is not machine specific and can be used in lieu of life testing approaches. By applying a building block approach at the systems level, the machine complexity was broken down to manageable levels independent of system implementation.
A recently initiated research project concerned with the concurrent detection of software errors and errors due to physical failures in the hardware of multiprocessor systems is described in this paper. An approach to error detection is described, which is specification based and relies on the structural verification of program control flow and data structure integrity. The techniques discussed utilize the hardware redundancy inherent in parallel processing systems to provide verification of both program structure and data concurrently with program execution.
Multiprocessor and Distributed Processing Bibliography package consists of large machine-readable bibliographic data base, which in addition to usual keyword searches, used for producing citations, indexes, and cross-references. Data base contains UNIX(R) "refer" -formatted ASCII data and implemented on any computer running under UNIX(R) operating system. Easily convertible to other operating systems. Requires approximately one megabyte of secondary storage. Bibliography compiled in 1985.
One of the most important issues in parallel processing is the mapping of workload to processors. This paper considers a large class of problems having a high degree of potential fine grained parallelism, and execution requirements that are either not predictable, or are too costly to predict. The main issues in mapping such a problem onto medium scale multiprocessors are those of aggregation and assignment. We study a method of parameterized aggregation that makes few assumptions about the workload. The mapping of aggregate units of work onto processors is uniform, and exploits locality of workload intensity to balance the unknown workload. In general, a finer aggregate granularity leads to a better balance at the price of increased communication/synchronization costs; the aggregation parameters can be adjusted to find a reasonable granularity. The effectiveness of this scheme is demonstrated on three model problems: an adaptive one-dimensional fluid dynamics problem with message passing, a sparse triangular linear system solver on both a shared memory and a message-passing machine, and a two-dimensional time-driven battlefield simulation employing message passing. Using the model problems, the tradeoffs are studied between balanced workload and the communication/synchronization costs. Finally, an analytical model is used to explain why the method balances workload and minimizes the variance in system behavior.
The use of Redundant Asynchronous Multiprocessor System to achieve ultrareliable Fault Tolerant Control Systems shows great promise. The development has been hampered by the inability to determine whether differences in the outputs of redundant CPU's are due to failures or to accrued error built up by slight differences in CPU clock intervals. This study derives an analytical dynamic model of the difference between redundant CPU's due to differences in their clock intervals and uses this model with on-line parameter identification to idenitify the differences in the clock intervals. The ability of this methodology to accurately track errors due to asynchronisity generate an error signal with the effect of asynchronisity removed and this signal may be used to detect and isolate actual system failures.
Problem partitioning of regular computation over two dimensional meshes on multiprocessor systems is examined. The regular computation model considered involves repetitive evaluation of values at each mesh point with local communication. The computational workload and the communication pattern are the same at each mesh point. The regular computation model arises in numerical solutions of partial differential equations and simulations of cellular automata. Given a communication pattern, a systematic way to generate a family of partitions is presented. The influence of various partitioning schemes on performance is compared on the basis of computation to communication ratio.
Multiple microcomputer system used to investigate application of parallel processing to real-time simulation. With dual-base architecture, each microcomputer communicates with corresponding microcomputer on opposite bus through dual-port interface memory. Transfers of data to and from front-end processor occur on interactive information bus. Transfers of data related to simulation calculations occur on real-time-information bus. System, called the real-time multiprocessor simulator (RTMPS), is tool for developing low-cost, portable, user-friendly simulators.
The problem of fault diagnosis in multiprocessor systems is considered under a uniformly probabilistic model in which processors are faulty with probability p. This work focuses on minimizing the number of tests that must be conducted in order to correctly diagnose the state of every processor in the system with high probability. A diagnosis algorithm that can correctly diagnose the state of every processor with probability approaching one in a class of systems performing slightly greater than a linear number of tests is presented. A nearly matching lower bound on the number of tests required to achieve correct diagnosis in arbitrary systems is also proven. The number of tests required under this probabilistic model is shown to be significantly less than under a bounded-size fault set model. Because the number of tests that must be conducted is a measure of the diagnosis overhead, these results represent a dramatic improvement in the performance of system-level diagnosis technique.
A computational procedure is presented for the nonlinear dynamic analysis of unsymmetric structures on vector multiprocessor systems. The procedure is based on a novel hierarchical partitioning strategy in which the response of the unsymmetric and antisymmetric response vectors (modes), each obtained by using only a fraction of the degrees of freedom of the original finite element model. The three key elements of the procedure which result in high degree of concurrency throughout the solution process are: (1) mixed (or primitive variable) formulation with independent shape functions for the different fields; (2) operator splitting or restructuring of the discrete equations at each time step to delineate the symmetric and antisymmetric vectors constituting the response; and (3) two level iterative process for generating the response of the structure. An assessment is made of the effectiveness of the procedure on the CRAY X-MP/4 computers.
A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.
A multiprocessor system, under design for space-station applications, makes use of the latest generation symbolic processor and packaging technology. The result will be a compact, space-qualified system two to three orders of magnitude more powerful than present-day symbolic processing systems.
Communication requirements of Cholesky factorization of dense and sparse symmetric, positive definite matrices are analyzed. The communication requirement is characterized by the data traffic generated on multiprocessor systems with local and shared memory. Lower bound proofs are given to show that when the load is uniformly distributed the data traffic associated with factoring an n x n dense matrix using n to the alpha power (alpha less than or equal 2) processors is omega(n to the 2 + alpha/2 power). For n x n sparse matrices representing a square root of n x square root of n regular grid graph the data traffic is shown to be omega(n to the 1 + alpha/2 power), alpha less than or equal 1. Partitioning schemes that are variations of block assignment scheme are described and it is shown that the data traffic generated by these schemes are asymptotically optimal. The schemes allow efficient use of up to O(n to the 2nd power) processors in the dense case and up to O(n) processors in the sparse case before the total data traffic reaches the maximum value of O(n to the 3rd power) and O(n to the 3/2 power), respectively. It is shown that the block based partitioning schemes allow a better utilization of the data accessed from shared memory and thus reduce the data traffic than those based on column-wise wrap around assignment schemes.