Multicore Challenges and Benefits for High Performance Scientific Computing

Nielsen, Ida M. B.; Janssen, Curtis L.

doi:10.1155/2008/450818

Title: Multicore Challenges and Benefits for High Performance Scientific Computing

Full Record
Other Related Research

Abstract

Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.

Authors:

Nielsen, Ida M. B. ^[1]; Janssen, Curtis L. ^[1]

Sandia National Laboratories, P.O. Box 969, Livermore, CA 94551, USA

Publication Date:: Tue Jan 01 00:00:00 EST 2008

Sponsoring Org.:: USDOE

OSTI Identifier:: 1197988

Grant/Contract Number:: DEAC04-94AL85000

Resource Type:: Published Article

Journal Name:: Scientific Programming

Additional Journal Information:: Journal Name: Scientific Programming Journal Volume: 16 Journal Issue: 4; Journal ID: ISSN 1058-9244

Publisher:: Hindawi Publishing Corporation

Country of Publication:: Egypt

Language:: English

Citation Formats


                    Nielsen, Ida M. B., and Janssen, Curtis L. Multicore Challenges and Benefits for High Performance Scientific Computing.  Egypt: N. p., 2008. 
Web.  doi:10.1155/2008/450818.

Copy to clipboard


                    Nielsen, Ida M. B., & Janssen, Curtis L. Multicore Challenges and Benefits for High Performance Scientific Computing.  Egypt.  https://doi.org/10.1155/2008/450818

Copy to clipboard


                    Nielsen, Ida M. B., and Janssen, Curtis L. Tue .  
"Multicore Challenges and Benefits for High Performance Scientific Computing".  Egypt.  https://doi.org/10.1155/2008/450818.

Copy to clipboard


                    
@article{osti_1197988,

  title        = {Multicore Challenges and Benefits for High Performance Scientific Computing},

  author       = {Nielsen, Ida M. B. and Janssen, Curtis L.},

  abstractNote = {Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will here discuss the architecture of parallel computers constructed from many multicore chips as well as techniques for managing the complexity of programming such computers, including the hybrid message-passing/multi-threading programming model. We will illustrate these ideas with a hybrid distributed memory matrix multiply and a quantum chemistry algorithm for energy computation using Møller–Plesset perturbation theory.},

  doi          = {10.1155/2008/450818},

  journal      = {Scientific Programming},

  number       = 4,

  volume       = 16,

  place        = {Egypt},

  year         = {Tue Jan 01 00:00:00 EST 2008},

  month        = {Tue Jan 01 00:00:00 EST 2008}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Publisher's Version of Record
https://doi.org/10.1155/2008/450818

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 5 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Complexity in scalable computing.

Journal Article Rouson, Damian W. I. - Proposed for publication in Scientific Programming.

The rich history of scalable computing research owes much to a rapid rise in computing platform scale in terms of size and speed. As platforms evolve, so must algorithms and the software expressions of those algorithms. Unbridled growth in scale inevitably leads to complexity. This special issue grapples with two facets of this complexity: scalable execution and scalable development. The former results from efficient programming of novel hardware with increasing numbers of processing units (e.g., cores, processors, threads or processes). The latter results from efficient development of robust, flexible software with increasing numbers of programming units (e.g., procedures, classes, componentsmore »« less
https://doi.org/10.1155/2008/693705
Data Locality Enhancement of Dynamic Simulations for Exascale Computing (Final Report)

Technical Report Shen, Xipeng

The development of modern processors exhibits two trends that complicate the optimizations of modern software. The first is the increasing sensitivity of processors' throughput to irregularities in computation. With more processors produced through a massive integration of simple cores, future systems will increasingly favor regular data-level parallel computations, but deviate from the needs of applications with complex patterns. Some evidences are already shown on Graphic Processing Units (GPU): Irregular data accesses (e.g., indirect references A[D[i]]) and conditional branches are limiting many GPU applications' performance at a level an order of magnitude lower than the peak of GPU. The second hardwaremore »« less
https://doi.org/10.2172/1576175

Full Text Available
Understanding and Mitigating Multicore Performance Issues on theAMD Opteron Architecture

Technical Report Levesque, John ; Larkin, Jeff ; Foster, Martyn ; ...

Over the past 15 years, microprocessor performance hasdoubled approximately every 18 months through increased clock rates andprocessing efficiency. In the past few years, clock frequency growth hasstalled, and microprocessor manufacturers such as AMD have moved towardsdoubling the number of cores every 18 months in order to maintainhistorical growth rates in chip performance. This document investigatesthe ramifications of multicore processor technology on the new Cray XT4?systems based on AMD processor technology. We begin by walking throughthe AMD single-core and dual-core and upcoming quad-core processorarchitectures. This is followed by a discussion of methods for collectingperformance counter data to understand code performance onmore »« less
https://doi.org/10.2172/918496

Full Text Available
MULTI-CORE AND OPTICAL PROCESSOR RELATED APPLICATIONS RESEARCH AT OAK RIDGE NATIONAL LABORATORY

Conference Barhen, Jacob ; Kerekes, Ryan A ; ST Charles, Jesse Lee ; ...

High-speed parallelization of common tasks holds great promise as a low-risk approach to achieving the significant increases in signal processing and computational performance required for next generation innovations in reconfigurable radio systems. Researchers at the Oak Ridge National Laboratory have been working on exploiting the parallelization offered by this emerging technology and applying it to a variety of problems. This paper will highlight recent experience with four different parallel processors applied to signal processing tasks that are directly relevant to signal processing required for SDR/CR waveforms. The first is the EnLight Optical Core Processor applied to matched filter (MF) correlationmore »« less
The Future Looks Bright for Teraflop Computing

Journal Article Farber, Rob - Scientific Computing, 24(10):34

Wouldn’t it be great to have a teraflop of computing power sitting in your lab, desktop workstation, or remote instrument server? Talk about simplifying workflows, eliminating competition for HPC resources, and allowing more scientists and technicians to get more work done! Well, the computer industry is marketing that capability now in the form of high-end video cards – and for a bargain price – with more and better technology on the market horizon. As the industry evolves to become more oriented toward multi-core and multi-threaded hardware; video card manufacturers are attempting to transition from a niche to multi-purpose market. Onemore »« less

Similar Records