3 edition of Communication overhead on the Intel iPSC-860 hypercube found in the catalog.
Communication overhead on the Intel iPSC-860 hypercube
Shahid H. Bokhari
by National Aeronautics and Space Administration, Langley Research Center in Hampton, Va
Written in English
|Series||ICASE interim report -- 10., NASA contractor report -- 182055., ICASE interim report -- no. 10., NASA contractor report -- NASA CR-182055.|
|Contributions||Langley Research Center.|
|The Physical Object|
Proposes a new approach for computing multidimensional DFTs that reduces interprocessor communications and is therefore suitable for efficient implementation on a variety of multiprocessor platforms including MIMD supercomputers and clusters of by: This is an introductory book on supercomputer applications written by a researcher who is working on solving scientific and engineering application problems on parallel computers. The book is intended to quickly bring researchers and graduate students working on numerical solutions of partial differential equations with various applications into the area of parallel book .
Section 5 we will describe how these communication strategies are actually implemented in multicomputers and will show how edge contention arises in circuit-switched machines. Measured timings of overhead due to edge contention on the Intel iPSC hypercube will be presented. Communications Ncube/2 and Intel hypercubes (iPSC/2 and iPSC/) are very similar in commun ication mechanisms. They have similar communication hardware and similar communi cation libraries. However, the Intel hypercubes uses .
hypercube machines such as Intel's iPSC/ 3 All-to-all personalized communication There are a total of N (N — 1) distinct messages to be moved among the processors to complete this operation. The simplistic approach of sending data along a Hamiltonian cycle of Qn, which works for all-to-all broadcasting. Parallel implementation of many-body mean-field equations: and other elementary operations, which we perform on a number of different computing architectures, including the Intel Paragon and the Intel iPSC/ hypercube. We discuss the approach to the problems of limited node memory and node-to-node communication overhead inherent in.
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Communication overhead on the Intel iPSC hypercube. [Shahid H Bokhari; Langley Research Center.]. Experiments were conducted on the Intel iPSC hypercube in order to evaluate the overhead of interprocessor : Shahid H.
Bokhari. In this paper, new functions that enable efficient intercube communication on the Intel iPSC/ are introduced. Communication between multiple cubes (power-of-two number of processor nodes.
The performance of the Intel iPSC/ hypercube is contrasted with earlier hypercubes from Intel and Ncube. Computation and communication performance for a number of low-level benchmarks are presented for the Intel iPSC/1 hypercube, the Ncube hypercube, the Intel iPSC/2 hypercube, and the new Intel iPSC/ hypercube.
The performance of the Intel iPSC/ hypercube and the Ncube hypercube are compared with earlier hypercubes from Intel and Ncube. Computation and communication performance for a number of low-level benchmarks are presented for the Intel iPSC/1, iPSC/2, and iPSC/ and for the Ncube and Cited by: The implementation of complete exchange on the circuit switched Intel iPSC hypercube is described.
This pattern, also known as all-to-all personalized communication, is the densest requirement that can be imposed on a : Shahid H. Bokhari. The iPSC/ consisted of up to processing elements connected in a hypercube, each element consisting of an Intel i at 40–50 MHz or Intel microprocessor.
Memory per node was increased to 8 MB and a similar Direct-Connect Module was used, which limited the size to nodes. Intel iPSC/ nodes, GFlops peak (MSR ORNL and CS UTK) Intel iPSC2 64 nodes, (CS UTK) Processors The iPSC/ is a high performance parallel computer system.
The processing power of the iPSC/ comes from its processing nodes. Each node in the iPSC/ is either a CX or an RX processor. The Intel iPSC/ Machine type: RISC-based distributed-memory multi-processor. Models: iPSC/iPSC/ Operating system: NX/2 node OS (transparent to the user and Unix on the front-end system.
Connection structure: Hypercube. Compilers: Fortran 77 and C with extensions. System parameters. Performance. The system is front-ended by the Systems. Experiments have been conducted on the Intel iPSC hypercube in order to evaluate the overhead of interprocessor communication.
It is demonstrated that (1) contrary to popular belief, the distance between two communicating processors has a significant impact on.
The offload overhead will be included in part of the communication overhead in this book. The fourth component to this equation is load balance and work division granularities. An imbalanced implementation of the algorithm can lead to sever performance degradations. RESULTS Calculations are being done on the Intel iPSC/ (RX) hypercube, which was delivered to Oak Ridge National Laboratory on 2 January This machine has processors and uses the i chip with a clock rate of 40 MHz.
The peak aggregate gigaflops is for double precision, l0 for single precision, Cited by: 1. The implementation of complete exchange on the circuit switched Intel iPSC hypercube is described.
This pattern, also known as all-to-all personalized communication, is the densest requirement that can be imposed on a network. Performance Study of LU Factorization with Low Communication Overhead on Multiprocessors.
the Intel iPSC/ hypercube is contrasted with earlier hypercubes from Intel and Ncube. A detailed theoretical runtime analysis using appropriate primitives for communication considers exact runtime, overhead and speedup for a hypercube architecteure.
Experiments on the Intel iPSC/ shows the numerical evidence of the theoretically computed runtimes. S. Bokhari. Communication overhead on the intel iPSC Hypercube. ICASE Interim Rep NASA Contractor ReportInstitute for Computer Applications in Science and Engineering, NASA Langley Research Center, Hampton, VAMay Google ScholarAuthor: Thomas Fahringer.
All numerical procedures reduce to a series of matrix-vector operations which we perform on the Intel iPSC/ hypercube, making full use of parallelism.
We discuss solutions to the problems of limited node memory and node-to-node communication overhead inherent in using distributed-memory, multiple-instruction, multiple-data stream parallel Cited by: 4. BOKHARI, S b Communication overhead on the Intel iPSC hypercube Tech Rep.
10, ICASE, NASA, Langley Research Center, Va Google Scholar BOKHAIti, S. Partitioning problems in parallel, pipelined and distributed computing IEEE Trans. Comput C, 1, 48 Author: G NormanMichael, ThanischPeter.
A new approach for computing multidimensional DFT's on parallel machines and its implementation on the iPSC/ hypercube Abstract: Proposes a new approach for computing multidimensional DFTs that reduces interprocessor communications and is therefore suitable for efficient implementation on a variety of multiprocessor platforms including MIMD Cited by:.
This paper presents the results of parallelizing a three-dimensional Navier-Stokes solver on a 32K-processor Thinking Machines CM-2, a node Intel iPSC/, and an 8-processor CRAY Y-MP. The main objective of this work is to study the performance of the flow solver, INS3D-LU code, on two distributed-memory machines, a massively parallel SIMD Cited by: 4.In this paper, we present the performance of a software video encoder with MPEG-2 quality on various parallel and distributed platforms.
The platforms include an Intel Paragon XP/S and an Intel iPSC/ hypercube parallel computer as well as Cited by: There were 64 nodes. Each node was a single board computer based on the Intel CPU and floating point coprocessor.
These were the chips that were being used in the IBM PC at the time. There was room on the board of the Cosmic Cube for only kilobytes of memory.