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Performance of image and video processing with general-purpose processors and media ISA extensions
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Source International Symposium on Computer Architecture archive
Proceedings of the 26th annual international symposium on Computer architecture table of contents
Atlanta, Georgia, United States
Pages: 124 - 135  
Year of Publication: 1999
ISBN:0-7695-0170-2
Also published in ...
Authors
Parthasarathy Ranganathan  Electrical and Computer Engineering, Rice University
Sarita Adve  Electrical and Computer Engineering, Rice University
Norman P. Jouppi  Western Research Laboratory, Compaq Computer Corporation
Sponsors
IEEE-CS\TCCA : TC on Computer Arhitecture
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 38,   Citation Count: 37
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ABSTRACT

This paper aims to provide a quantitative understanding of the performance of image and video processing applications on general-purpose processors, without and with media ISA extensions. We use detailed simulation of 12 benchmarks to study the effectiveness of current architectural features and identify future challenges for these workloads.Our results show that conventional techniques in current processors to enhance instruction-level parallelism (ILP) provide a factor of 2.3X to 4.2X performance improvement. The Sun VIS media ISA extensions provide an additional 1.1X to 4.2X performance improvement. The ILP features and media ISA extensions significantly reduce the CPU component of execution time, making 5 of the image processing benchmarks memory-bound.The memory behavior of our benchmarks is characterized by large working sets and streaming data accesses. Increasing the cache size has no impact on 8 of the benchmarks. The remaining benchmarks require relatively large cache sizes (dependent on the display sizes) to exploit data reuse, but derive less than 1.2X performance benefits with the larger caches. Software prefetching provides 1.4X to 2.5X performance improvement in the image processing benchmarks where memory is a significant problem. With the addition of software prefetching, all our benchmarks revert to being compute-bound.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  37

Collaborative Colleagues:
Parthasarathy Ranganathan: colleagues
Sarita Adve: colleagues
Norman P. Jouppi: colleagues