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On the use of fuzzy techniques in cache memory management

On the use of fuzzy techniques in cache memory management. Hassan Diab, Ulrich Furbach, Hassan Tabbara. Chun-Fu Kung System Laboratory, Department of Computer Engineering and Science, Yuan-Ze University, Taiwan, Republic of China 2000/7/12. Outline. Introduction Implementation Simulation

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On the use of fuzzy techniques in cache memory management

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  1. On the use of fuzzy techniques in cache memory management Hassan Diab, Ulrich Furbach, Hassan Tabbara Chun-Fu Kung System Laboratory, Department of Computer Engineering and Science, Yuan-Ze University, Taiwan, Republic of China 2000/7/12

  2. Outline • Introduction • Implementation • Simulation • Results • Conclusion

  3. Introduction • Cache memories (CM) are high-speed buffers which are inserted between the processor and main memory (MM) to capture those portions of the contents of MM. • The swapping of information between MM and CM requires a replacement algorithm (RA) to select a block frame (BF) to replace. • Four placement policies: direct, fully associative, set associative, and sector mapping.

  4. Sector mapping • MM is partitioned into a number of sectors, each composed of a number of blocks. • CM is partitioned into sector frames, each composed of a set of BFs. • Only the block that caused the cache miss is brought into the cache, and the remaining BFs in that sector are flagged as invalid. • The advantage of the mapping is that it reduce the cost of the map since it requires relatively few tags.

  5. FL and FC • Fuzzy logic (FL) and fuzzy control (FC) has proved to be a powerful tool when it is applied to ill-defined and complex systems. • The basic concept underlying FL is that of a linguistic variable. • FL systems deal with fuzzy consequents and/or fuzzy antecedents.

  6. Implementation • The FLRA used is composed of a 3-input and 1-output control system. • The inputs are the frequency of reference (FREF), the CM hit ratio (HR), and the sector age (AGE). The output is the block replacement index (BRI), calculated for each BF.

  7. Implementation (cont.) • Step 1. Fuzzify inputs • Step 2. Apply fuzzy operator • Step 3. Apply implication • Step 4. Aggregate all outputs • Step 5. Defuzzify

  8. Begin Y Read word from CM Increment FREF by one Word required in CM? N Y Sector that this block belong in CM? N Y Move the required Block from MM to CM Increment FREF by one Is there a place for a new sector in CM? Move the required block to CM N Use the RA to selected a sector to replace Read the word required From the block End

  9. Results Use the same load: 30% read, 20% write and 10% jump The CM is composed of 64 words per block

  10. Results (cont.) Load1: 15% read, 10% write and 5% jump Load1: 15% read, 5% write and 5% jump Load1: 5% read, 5% write and 5% jump CM: 16 words/block, 16 blocks/sector and 256 sectors

  11. Conclusion • We presented a fuzzy logic replacement algorithm (FLRA) for sector-mapped cache memory organization. • These 24 fuzzy inference rules may be tuned further using expert knowledge to attain a further improvement in the performance.

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