1. Computer Organization CS224 Fall 2012 Lessons 37 & 38

2. Memory Technology  Static RAM (SRAM) l 0.5ns – 2.5ns, $2000 – $5000 per GB  Dynamic RAM (DRAM) l 50ns – 70ns, $20 – $75 per GB  Magnetic disk l 5ms – 20ms, $0.20 – $2 per GB  Ideal memory l Access time of SRAM l Capacity and cost/GB of disk §5.1 Introduction

3. Principle of Locality  Programs access a small proportion of their address space at any time  Temporal locality l Items accessed recently are likely to be accessed again soon l e.g., instructions in a loop, induction variables  Spatial locality l Items near those accessed recently are likely to be accessed soon l E.g., sequential instruction access, array data

4. Taking Advantage of Locality  Memory hierarchy  Store everything on disk  Copy recently accessed (and nearby) items from disk to smaller DRAM memory l Main memory  Copy more recently accessed (and nearby) items from DRAM to smaller SRAM memory l Cache memory attached to CPU

5. Memory Hierarchy Levels  Block (aka line): unit of copying l May be multiple words  If accessed data is present in upper level l Hit: access satisfied by upper level -Hit ratio: hits/accesses  If accessed data is absent l Miss: block copied from lower level -Time taken: miss penalty -Miss ratio: misses/accesses = 1 – hit ratio l Then accessed data supplied from upper level

6. Cache Memory  Cache memory l The level of the memory hierarchy closest to the CPU  Given accesses X 1, …, X n–1, X n §5.2 The Basics of Caches  How do we know if the data is present?  Where do we look?

7. Direct Mapped Cache  Location determined by address  Direct mapped: only one choice l (Block address) modulo (#Blocks in cache)  #Blocks is a power of 2  Use low-order address bits

8. Tags and Valid Bits  How do we know which particular block is stored in a cache location? l Store block address as well as the data l Actually, only need the high-order bits l Called the tag  What if there is no data in a location? l Valid bit: 1 = present, 0 = not present l Initially 0

9. Cache Example  8-blocks, 1 word/block, direct mapped  Initial state IndexVTagData 000N 001N 010N 011N 100N 101N 110N 111N

10. Cache Example IndexVTagData 000N 001N 010N 011N 100N 101N 110Y10Mem[10110] 111N Word addrBinary addrHit/missCache block 2210 110Miss110

11. Cache Example IndexVTagData 000N 001N 010Y11Mem[11010] 011N 100N 101N 110Y10Mem[10110] 111N Word addrBinary addrHit/missCache block 2611 010Miss010

12. Cache Example IndexVTagData 000N 001N 010Y11Mem[11010] 011N 100N 101N 110Y10Mem[10110] 111N Word addrBinary addrHit/missCache block 2210 110Hit110 2611 010Hit010

13. Cache Example IndexVTagData 000Y10Mem[10000] 001N 010Y11Mem[11010] 011Y00Mem[00011] 100N 101N 110Y10Mem[10110] 111N Word addrBinary addrHit/missCache block 1610 000Miss000 300 011Miss011 1610 000Hit000

14. Cache Example IndexVTagData 000Y10Mem[10000] 001N 010Y10Mem[10010] 011Y00Mem[00011] 100N 101N 110Y10Mem[10110] 111N Word addrBinary addrHit/missCache block 1810 010Miss010

15. Address Subdivision

16. Example: Larger Block Size  64 blocks, 16 bytes/block l To what block number does address 1200 map?  Block address =  1200/16  = 75  Block number = 75 modulo 64 = 11 TagIndexOffset 03491031 4 bits6 bits22 bits

17. Block Size Considerations  Larger blocks should reduce miss rate l Due to spatial locality  But in a fixed-sized cache l Larger blocks  fewer of them -More competition  increased miss rate l Larger blocks  pollution  Larger miss penalty l Can override benefit of reduced miss rate l Early restart and critical-word-first can help

18. Cache Misses  On cache hit, CPU proceeds normally  On cache miss l Stall the CPU pipeline l Fetch block from next level of hierarchy l Instruction cache miss -Restart instruction fetch l Data cache miss -Complete data access