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The hardness of cache conscious data placement
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Source Annual Symposium on Principles of Programming Languages archive
Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages table of contents
Portland, Oregon
Pages: 101 - 112  
Year of Publication: 2002
ISBN:1-58113-450-9
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Authors
Erez Petrank  Technion - Israel Institute of Technology, Haifa 32000, Israel
Dror Rawitz  Technion - Israel Institute of Technology, Haifa 32000, Israel
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 65,   Citation Count: 17
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ABSTRACT

The growing gap between the speed of memory access and cache access has made cache misses an influential factor in program efficiency. Much effort has been spent recently on reducing the number of cache misses during program run. This effort includes wise rearranging of program code, cache-conscious data placement, and algorithmic modifications that improve the program cache behavior. In this work we investigate the complexity of finding the optimal placement of objects (or code) in the memory, in the sense that this placement reduces the cache misses to the minimum. We show that this problem is one of the toughest amongst the interesting algorithmic problems in computer science. In particular, suppose one is given a sequence of memory accesses and one has to place the data in the memory so as to minimize the number of cache misses for this sequence. We show that if P ≠ NP, then one cannot efficiently approximate the optimal solution even up to a very liberal approximation ratio. Thus, this problem joins the small family of extremely inapproximable optimization problems. The other two famous members in this family are minimum coloring and maximum clique.


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  17

Collaborative Colleagues:
Erez Petrank: colleagues
Dror Rawitz: colleagues