1. Memory Hierarchy and Cache Design The following sources are used for preparing these slides: Lecture 14 from the course Computer architecture ECE 201 by Professor Mike Schulte.Computer architecture ECE 201 Lecture 4 from William Stallings, Computer Organization and Architecture, Prentice Hall; 6th edition, July 15, 2002. Lecture 6 from the course Systems Architectures II by Professors Jeremy R. Johnson and Anatole D. Ruslanov Some of figures are from Computer Organization and Design: The Hardware/Software Approach, Third Edition, by David Patterson and John Hennessy, are copyrighted material (COPYRIGHT 2004 MORGAN KAUFMANN PUBLISHERS, INC. ALL RIGHTS RESERVED).

2. Memory Hierarchy Memory technologyTypical access time$ per GB in 2004 SRAM0.5–5 ns$4000–$10,000 DRAM50–70 ns$100–$200 Magnetic disk5,000,000–20,000,000 ns$0.50–$2

3. SRAM v DRAM Both volatile –Power needed to preserve data Dynamic cell –Simpler to build, smaller –More dense –Less expensive –Needs refresh –Larger memory units Static –Faster –Cache

4. General Principles of Memory Locality –Temporal Locality: referenced memory is likely to be referenced again soon (e.g. code within a loop) –Spatial Locality: memory close to referenced memory is likely to be referenced soon (e.g., data in a sequentially access array) Definitions –Upper: memory closer to processor –Block: minimum unit that is present or not present –Block address: location of block in memory –Hit: Data is found in the desired location –Hit time: time to access upper level –Miss rate: percentage of time item not found in upper level Locality + smaller HW is faster = memory hierarchy –Levels: each smaller, faster, more expensive/byte than level below –Inclusive: data found in upper level also found in the lower level

5. Cache Small amount of fast memory Sits between normal main memory and CPU May be located on CPU chip or module

6. Cache operation - overview CPU requests contents of memory location Check cache for this data If present, get from cache (fast) If not present, read required block from main memory to cache Then deliver from cache to CPU Cache includes tags to identify which block of main memory is in each cache slot

7. Cache/memory structure

8. Four Questions for Memory Hierarchy Designers Q1: Where can a block be placed in the upper level? (Block placement) Q2: How is a block found if it is in the upper level? (Block identification) Q3: Which block should be replaced on a miss? (Block replacement) Q4: What happens on a write? (Write strategy)

9. Q1: Where can a block be placed? Direct Mapped: Each block has only one place that it can appear in the cache. Fully associative: Each block can be placed anywhere in the cache. Set associative: Each block can be placed in a restricted set of places in the cache. –If there are n blocks in a set, the cache placement is called n-way set associative What is the associativity of a direct mapped cache?

10. Associativity Examples Cache size is 8 blocks Where does word 12 from memory go? Fully associative: Block 12 can go anywhere Direct mapped: Block no. = (Block address) mod (No. of blocks in cache) Block 12 can go only into block 4 (12 mod 8 = 4) => Access block using lower 3 bits 2-way set associative: Set no. = (Block address) mod (No. of sets in cache) Block 12 can go anywhere in set 0 (12 mod 4 = 0) => Access set using lower 2 bits

11. Mapping: memory mapped to one location in cache: (Block address) mod (Number of blocks in cache) Number of blocks is typically a power of two, i.e., cache location obtained from low-order bits of address. Direct Mapped Cache

12. Locating data in the Cache Index is 10 bits, while tag is 20 bits –We need to address 1024 (2 10 ) words –We could have any of 2 20 words per cache location Valid bit indicates whether an entry contains a valid address or not Tag bits is usually indicated by address size – (log 2 (memory size) + 2) –E.g. 32 – (10 + 2) = 20

13. Q2: How Is a Block Found? The address can be divided into two main parts –Block offset: selects the data from the block offset size = log2(block size) –Block address: tag + index »index: selects set in cache index size = log2(#blocks/associativity) »tag: compared to tag in cache to determine hit tag size = addreess size - index size - offset size Each block has a valid bit that tells if the block is valid - the block is in the cache if the tags match and the valid bit is set. TagIndex

14. Q4: What Happens on a Write? Write through: The information is written to both the block in the cache and to the block in the lower-level memory. Write back: The information is written only to the block in the cache. The modified cache block is written to main memory only when it is replaced. –is block clean or dirty? (add a dirty bit to each block) Pros and Cons of each: –Write through »Read misses cannot result in writes to memory, »Easier to implement »Always combine with write buffers to avoid memory latency –Write back »Less memory traffic »Perform writes at the speed of the cache

15. Reducing Cache Misses with a more Flexible Replacement Strategy In a direct mapped cache a block can go in exactly one place in cache In a fully associative cache a block can go anywhere in cache A compromise is to use a set associative cache where a block can go into a fixed number of locations in cache, determined by: (Block number) mod (Number of sets in cache)

16. Example Three small 4 word caches: Direct mapped, two-way set associative, fully associative How many misses in the sequence of block addresses: 0, 8, 0, 6, 8? How does this change with 8 words, 16 words?

17. Locating a Block in Cache Check the tag of every cache block in the appropriate set Address consists of 3 parts Replacement strategy: E.G. Least Recently Used (LRU)

18. Size of Tags vs. Associativity Increasing associativity requires more comparators, as well as more tag bits per cache block. Assume a cache with 4K 4-word blocks and 32 bit addresses Find the total number of sets and the total number of tag bits for a –direct mapped cache –two-way set associative cache –four-way set associative cache –fully associative cache

19. Size of Tags vs. Associativity Total cache size 4K x 4 words/block x 4 bytes/word = 64Kb Direct mapped cache: –16 bytes/block  28 bits for tag and index –# sets = # blocks –Log(4K) = 12 bits for index  16 bits for tag –Total # of tag bits = 16 bits x 4K locations = 64 Kbits Two-way set-associative cache: –32 bytes / set –16 bytes/block  28 bits for tag and index –# sets = # blocks / 2  2K sets –Log(2K) = 11 bits for index  17 bits for tag –Total # of tag bits = 17 bits x 2 location / set x 2K sets = 68 Kbits

20. Size of Tags vs. Associativity Four-way set-associative cache: –64 bytes / set –16 bytes/block  28 bits for tag and index –# sets = # blocks / 4  1K sets –Log(1K) = 10 bits for index  18 bits for tag –Total # of tag bits = 18 bits x 4 location / set x 1K sets = 72 Kbits Fully associative cache: –1 set of 4 K blocks  28 bits for tag and index –Index = 0 bits  tag will have 28 bits –Total # of tag bits = 28 bits x 4K location / set x 1 set = 112 Kbits

21. Measuring Cache Performance CPU time = (CPU execution clock cycles + Memory stall clock cycles)  Clock-cycle time Memory stall clock cycles = Read-stall cycles + Write-stall cycles Read-stall cycles = Reads/program  Read miss rate  Read miss penalty Write-stall cycles = (Writes/program  Write miss rate  Write miss penalty) + Write buffer stalls (assumes write-through cache) Write buffer stalls should be negligible and write and read miss penalties equal (cost to fetch block from memory) Memory stall clock cycles = Mem access/program  miss rate  miss penalty

22. Example I Assume I-miss rate of 2% and D-miss rate of 4% (gcc) Assume CPI = 2 (without stalls) and miss penalty of 40 cycles Assume 36% loads/stores What is the CPI with memory stalls? How much faster would a machine with perfect cache run? What happens if the processor is made faster, but the memory system stays the same (e.g. reduce CPI to 1)?

23. Calculation I Instruction miss cycles = I x 100% x 2% x 40 =.80 x I Data miss cycles = I x 36% x 4% x 40 =.58 x I Total miss cycles =.80 x I +.58 x I = 1.38 x I CPI = 2 + 1.38 = 3.38 Perf Perf / Perf Stall = 3.38/2 = 1.69 For a processor with base CPI = 1: CPI = 1 + 1.38 = 2.38  Perf Perf / Perf Stall = 2.38 Time spent on stalls for slower processor 1.38/3.38 = 41% Time spent on stalls for faster processor 1.38/2.38 = 58%