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On the use of fuzzy techniques in cache memory management Chun-Fu Kung System Laboratory, Department of Computer Engineering and Science, Yuan-Ze University,

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Presentation on theme: "On the use of fuzzy techniques in cache memory management Chun-Fu Kung System Laboratory, Department of Computer Engineering and Science, Yuan-Ze University,"— Presentation transcript:

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

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.

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

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

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

12 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

13 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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