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ITR: A High-Performance Compression Infrastructure for Extended Program Traces

ITR: A High-Performance Compression Infrastructure for Extended Program Traces
ITR:用于扩展程序跟踪的高性能压缩基础设施
批准号:
0312966
负责人:
Martin Burtscher
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-01 至 2006-08-31

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中文摘要
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英文摘要
BurtscherA High-Performance Compression Infrastructure for Extended Program TracesAbstractProgram execution traces are widely used by researchers and educators to study program and processor behavior. Unfortunately, even capturing only a byte of information per executed instruction generates on the order of a gigabyte of data per second on a modern high-end microprocessor. Hence, nontrivial traces need to be stored in compressed form to be manageable. While good compression schemes exist for traces that capture only the PCs of the executed instructions, these schemes can be ineffective on extended traces that include important additional information such as the content of registers, effective addresses, values on a bus, etc. We propose to employ techniques from the value-prediction literature to compress extended traces. Preliminary results show that our approach delivers substantially improved compression rates on the traces where it matters the most, i.e., on the traces that other algorithms cannot compress well. The extended information is important because it encapsulates the parameters that are of interest in many current research endeavors. To enable the utilization of this kind of information in the classroom and the laboratory, high-performance compression tools need to be developed and made publicly available. This is the primary goal of this proposal. The tool will allow students and researchers alike to gain a better understanding of real programs and processors, and will promote the teaching and learning about these topics. It will be made available on the Web along with commented source code, documentation, and a tutorial. Moreover, the inner workings of the compression algorithm will be publicized and disseminated in research papers to encourage the usage as well as further studies of the compression algorithm.
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Collaborative Research: SHF: Medium: Practical and Rigorous Correctness Checking and Correctness Preservation for Irregular Parallel Programs
  • 批准号:
    1955367
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $30.25万
  • 财政年份:
    2020
  • 负责人:
    Martin Burtscher
  • 依托单位:
CSR: Medium: Collaborative Research: Programming Abstractions and Systems Support for GPU-Based Acceleration of Irregular Applications
  • 批准号:
    1406304
  • 项目类别:
    Standard Grant
  • 资助金额:
    $36.0万
  • 财政年份:
    2014
  • 负责人:
    Martin Burtscher
  • 依托单位:
XPS: EXPL: CCA: Collaborative Research: Nixing Scale Bugs in HPC Applications
  • 批准号:
    1438963
  • 项目类别:
    Standard Grant
  • 资助金额:
    $15.0万
  • 财政年份:
    2014
  • 负责人:
    Martin Burtscher
  • 依托单位:
CSR: Small: Collaborative Research: Real-Time Unobtrusive Tracing in Multicore Embedded Systems
  • 批准号:
    1217231
  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.3万
  • 财政年份:
    2012
  • 负责人:
    Martin Burtscher
  • 依托单位:
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