Aspects of Cache Memory and Instruction Buffer Performance
CALIFORNIA UNIV BERKELEY DEPT OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
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Techniques are developed in this dissertation to efficiently evaluate direct-mapped and set-associative caches. These techniques are used to study associativity in CPU caches and examine instruction caches for single-chip RISC microprocessors. This research is motivated in general by the importance of cache memories to computer performance, and more specifically by work done to design the caches in SPUR, a multiprocessor workstation designed at U.C. Berkeley. The studies focus not only on abstract measures of performance such as miss ratios, but also include, when appropriate, detailed implementation factors, such as access times and gate delays. The simulation algorithms developed compute miss ratios for numerous alternative caches with one pass through an address trace, provided all caches have the same block size, and use demand fetching and LRU replacement. One algorithm forest simulation simulates direct-mapped caches by relying on inclusion, a property that all larger caches contain a superset of the data in smaller caches. The other algorithm all associativity simulation simulates a broader class of direct-mapped and set-associative caches than could previously be studied with a one-pass algorithm, although somewhat less efficiently than forest simulation, since inclusion does not hold. The analysis of set-associative caches yields two major results. First, constant factors are obtained which relate the miss ratios for set-associative caches to miss ratios for other set-associative caches. Then those results are combined with sample cache implementations to show that above certain cache sizes, direct-mapped caches have lower effective access times than set-associative caches, despite having higher miss ratios. Finally, instruction buffers and target instruction buffers are examined as organizations for instruction memory on single-chip microprocessors.
- Computer Hardware
- Machinery and Tools