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V. Venkatakrishnan

Bio: V. Venkatakrishnan is an academic researcher from Ames Research Center. The author has contributed to research in topics: Intel iPSC & MIMD. The author has an hindex of 4, co-authored 4 publications receiving 2778 citations.

Papers
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Journal ArticleDOI
01 Sep 1991
TL;DR: A new set of benchmarks has been developed for the performance evaluation of highly parallel supercom puters that mimic the computation and data move ment characteristics of large-scale computational fluid dynamics applications.
Abstract: A new set of benchmarks has been developed for the performance evaluation of highly parallel supercom puters. These consist of five "parallel kernel" bench marks and three "simulated application" benchmarks. Together they mimic the computation and data move ment characteristics of large-scale computational fluid dynamics applications. The principal distinguishing feature of these benchmarks is their "pencil and paper" specification-all details of these benchmarks are specified only algorithmically. In this way many of the difficulties associated with conventional bench- marking approaches on highly parallel systems are avoided.

2,246 citations

Journal ArticleDOI
25 Mar 1991
TL;DR: A mesh-vertex finite volume scheme for solving the Euler equations on triangular unstructured meshes is implemented on a MIMD (multiple instruction/multiple data stream) parallel computer and it is found that the spectral bisection strategy yields the best performance.
Abstract: A mesh-vertex finite volume scheme for solving the Euler equations on triangular unstructured meshes is implemented on a MIMD (multiple instruction/multiple data stream) parallel computer. Three partitioning strategies for distributing the work load onto the processors are discussed. Issues pertaining to the communication costs are also addressed. We find that the spectral bisection strategy yields the best performance. The performance of this unstructured computation on the Intel iPSC/860 compares very favorably with that on a one-processor CRAY Y-MP/1 and an earlier implementation on the Connection Machine.

85 citations


Cited by
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Book
01 Apr 2003
TL;DR: This chapter discusses methods related to the normal equations of linear algebra, and some of the techniques used in this chapter were derived from previous chapters of this book.
Abstract: Preface 1. Background in linear algebra 2. Discretization of partial differential equations 3. Sparse matrices 4. Basic iterative methods 5. Projection methods 6. Krylov subspace methods Part I 7. Krylov subspace methods Part II 8. Methods related to the normal equations 9. Preconditioned iterations 10. Preconditioning techniques 11. Parallel implementations 12. Parallel preconditioners 13. Multigrid methods 14. Domain decomposition methods Bibliography Index.

13,484 citations

Book
15 Aug 1998
TL;DR: This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures and provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions.
Abstract: The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a common machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures. It then examines the design issues that are critical to all parallel architecture across the full range of modern design, covering data access, communication performance, coordination of cooperative work, and correct implementation of useful semantics. It not only describes the hardware and software techniques for addressing each of these issues but also explores how these techniques interact in the same system. Examining architecture from an application-driven perspective, it provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions. * synthesizes a decade of research and development for practicing engineers, graduate students, and researchers in parallel computer architecture, system software, and applications development * presents in-depth application case studies from computer graphics, computational science and engineering, and data mining to demonstrate sound quantitative evaluation of design trade-offs * describes the process of programming for performance, including both the architecture-independent and architecture-dependent aspects, with examples and case-studies * illustrates bus-based and network-based parallel systems with case studies of more than a dozen important commercial designs Table of Contents 1 Introduction 2 Parallel Programs 3 Programming for Performance 4 Workload-Driven Evaluation 5 Shared Memory Multiprocessors 6 Snoop-based Multiprocessor Design 7 Scalable Multiprocessors 8 Directory-based Cache Coherence 9 Hardware-Software Tradeoffs 10 Interconnection Network Design 11 Latency Tolerance 12 Future Directions APPENDIX A Parallel Benchmark Suites

1,571 citations

Proceedings ArticleDOI
20 Jun 2009
TL;DR: This work proposes, crafted from a fundamental understanding of PCM technology parameters, area-neutral architectural enhancements that address these limitations and make PCM competitive with DRAM.
Abstract: Memory scaling is in jeopardy as charge storage and sensing mechanisms become less reliable for prevalent memory technologies, such as DRAM. In contrast, phase change memory (PCM) storage relies on scalable current and thermal mechanisms. To exploit PCM's scalability as a DRAM alternative, PCM must be architected to address relatively long latencies, high energy writes, and finite endurance.We propose, crafted from a fundamental understanding of PCM technology parameters, area-neutral architectural enhancements that address these limitations and make PCM competitive with DRAM. A baseline PCM system is 1.6x slower and requires 2.2x more energy than a DRAM system. Buffer reorganizations reduce this delay and energy gap to 1.2x and 1.0x, using narrow rows to mitigate write energy and multiple rows to improve locality and write coalescing. Partial writes enhance memory endurance, providing 5.6 years of lifetime. Process scaling will further reduce PCM energy costs and improve endurance.

1,568 citations

Book
11 Oct 2000
TL;DR: Aimed at the working researcher or scientific C/C++ or Fortran programmer, this text introduces the competent research programmer to a new vocabulary of idioms and techniques for parallelizing software using OpenMP.
Abstract: Aimed at the working researcher or scientific C/C++ or Fortran programmer, this text introduces the competent research programmer to a new vocabulary of idioms and techniques for parallelizing software using OpenMP.

1,253 citations

Book ChapterDOI
08 Apr 2002
TL;DR: The StreamIt language provides novel high-level representations to improve programmer productivity and program robustness within the streaming domain and the StreamIt compiler aims to improve the performance of streaming applications via stream-specific analyses and optimizations.
Abstract: We characterize high-performance streaming applications as a new and distinct domain of programs that is becoming increasingly important. The StreamIt language provides novel high-level representations to improve programmer productivity and program robustness within the streaming domain. At the same time, the StreamIt compiler aims to improve the performance of streaming applications via stream-specific analyses and optimizations. In this paper, we motivate, describe and justify the language features of StreamIt, which include: a structured model of streams, a messaging system for control, a re-initialization mechanism, and a natural textual syntax.

1,224 citations