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Kong et al., 2013 - Google Patents

When polyhedral transformations meet SIMD code generation

Kong et al., 2013

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Document ID
10448221129889353645
Author
Kong M
Veras R
Stock K
Franchetti F
Pouchet L
Sadayappan P
Publication year
Publication venue
Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation

External Links

Snippet

Data locality and parallelism are critical optimization objectives for performance on modern multi-core machines. Both coarse-grain parallelism (eg, multi-core) and fine-grain parallelism (eg, vector SIMD) must be effectively exploited, but despite decades of progress …
Continue reading at users.ece.cmu.edu (PDF) (other versions)

Classifications

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    • G06F8/4441—Reducing the execution time required by the program code
    • G06F8/4442—Reducing the number of cache misses; Data prefetching
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