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Automatic Extraction of Coarse-Grained Data-Flow Threads from Imperative Programs

Authors: Li, Feng; Pop, Antoniu; Cohen, Albert;

Automatic Extraction of Coarse-Grained Data-Flow Threads from Imperative Programs

Abstract

This article presents a general algorithm for transforming sequential imperative programs into parallel data-flow programs. The algorithm operates on a program dependence graph in static-single-assignment form, extracting task, pipeline, and data parallelism from arbitrary control flow, and coarsening its granularity using a generalized form of typed fusion. A prototype based on GNU Compiler Collection (GCC) is applied to the automatic parallelization of recursive C programs. © 1981-2012 IEEE.

Keywords

sequential imperative program transformation, data parallelism, imperative programs, program dependence graph, Synchronization, Instruction sets, data flow graphs, Parallel processing, Sequential analysis, GNU compiler collection, SSA form, automatic recursive C program parallelization, task extraction, program interpreters, data flow computing, arbitrary control flow, loop fusion, parallel programming, automatic parallelization, sequential imperative programs, program compilers, Radiation detectors, automatic coarse-grained data-flow thread extraction, [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Pipeline processing, parallel data-flow programs, data-flow model

  • BIP!
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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    19
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
19
Average
Top 10%
Top 10%
Green
bronze