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Empirical study of parallel lru simulation algorithms
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Carr, Eric Nicol, David M. |
| Copyright Year | 1994 |
| Description | This paper reports on the performance of five parallel algorithms for simulating a fully associative cache operating under the LRU (Least-Recently-Used) replacement policy. Three of the algorithms are SIMD, and are implemented on the MasPar MP-2 architecture. Two other algorithms are parallelizations of an efficient serial algorithm on the Intel Paragon. One SIMD algorithm is quite simple, but its cost is linear in the cache size. The two other SIMD algorithm are more complex, but have costs that are independent on the cache size. Both the second and third SIMD algorithms compute all stack distances; the second SIMD algorithm is completely general, whereas the third SIMD algorithm presumes and takes advantage of bounds on the range of reference tags. Both MIMD algorithm implemented on the Paragon are general and compute all stack distances; they differ in one step that may affect their respective scalability. We assess the strengths and weaknesses of these algorithms as a function of problem size and characteristics, and compare their performance on traces derived from execution of three SPEC benchmark programs. |
| File Size | 1207731 |
| Page Count | 17 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19950012612 |
| Archival Resource Key | ark:/13960/t6741q05g |
| Language | English |
| Publisher Date | 1994-10-01 |
| Access Restriction | Open |
| Subject Keyword | Computer Programming And Software Algorithms Simd Computers Performance Prediction Massively Parallel Processors Mimd Computers Computerized Simulation Architecture Computers Replacing Parallel Processing Computers Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Article |
