CS 61C L23 Caches IV / VM I (1) Garcia, Spring 2004 © UCB Lecturer PSOE Dan Garcia www.cs.berkeley.edu/~ddgarcia inst.eecs.berkeley.edu/~cs61c CS61C :

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CS 61C L23 Caches IV / VM I (1) Garcia, Spring 2004 © UCB Lecturer PSOE Dan Garcia inst.eecs.berkeley.edu/~cs61c CS61C : Machine Structures Lecture 23 – Caches IV / VM I Grand Challenge news!  Blue Team withdrew prior to start.  Red Team: At mile 7.4. Vehicle went off course, got caught on obstacle & front wheels caught fire! All withdrew/crashed by mile 7.4…

CS 61C L23 Caches IV / VM I (2) Garcia, Spring 2004 © UCB Review: Why We Use Caches µProc 60%/yr. DRAM 7%/yr DRAM CPU 1982 Processor-Memory Performance Gap: (grows 50% / year) Performance “Moore’s Law” 1989 first Intel CPU with cache on chip 1998 Pentium III has two levels of cache on chip

CS 61C L23 Caches IV / VM I (3) Garcia, Spring 2004 © UCB Review: Direct-Mapped Cache Example Recall this is how a simple direct mapped cache looked. Memory Memory Address A B C D E F 4 Byte Direct Mapped Cache Cache Index

CS 61C L23 Caches IV / VM I (4) Garcia, Spring 2004 © UCB Review: Associative Cache Example Here’s a simple 2 way set associative cache. Memory Memory Address A B C D E F Cache Index

CS 61C L23 Caches IV / VM I (5) Garcia, Spring 2004 © UCB Block Replacement Policy (1/2) Direct-Mapped Cache: index completely specifies position which position a block can go in on a miss N-Way Set Assoc: index specifies a set, but block can occupy any position within the set on a miss Fully Associative: block can be written into any position Question: if we have the choice, where should we write an incoming block?

CS 61C L23 Caches IV / VM I (6) Garcia, Spring 2004 © UCB Block Replacement Policy (2/2) If there are any locations with valid bit off (empty), then usually write the new block into the first one. If all possible locations already have a valid block, we must pick a replacement policy: rule by which we determine which block gets “cached out” on a miss.

CS 61C L23 Caches IV / VM I (7) Garcia, Spring 2004 © UCB Block Replacement Policy: LRU LRU (Least Recently Used) Idea: cache out block which has been accessed (read or write) least recently Pro: temporal locality  recent past use implies likely future use: in fact, this is a very effective policy Con: with 2-way set assoc, easy to keep track (one LRU bit); with 4-way or greater, requires complicated hardware and much time to keep track of this

CS 61C L23 Caches IV / VM I (8) Garcia, Spring 2004 © UCB Block Replacement Example We have a 2-way set associative cache with a four word total capacity and one word blocks. We perform the following word accesses (ignore bytes for this problem): 0, 2, 0, 1, 4, 0, 2, 3, 5, 4 How many hits and how many misses will there be for the LRU block replacement policy?

CS 61C L23 Caches IV / VM I (9) Garcia, Spring 2004 © UCB Block Replacement Example: LRU Addresses 0, 2, 0, 1, 4, 0,... 0 lru 2 1 loc 0loc 1 set 0 set 1 02 lru set 0 set 1 0: miss, bring into set 0 (loc 0) 2: miss, bring into set 0 (loc 1) 0: hit 1: miss, bring into set 1 (loc 0) 4: miss, bring into set 0 (loc 1, replace 2) 0: hit 0 set 0 set 1 lru 02 set 0 set 1 lru set 0 set lru 2 4 set 0 set lru

CS 61C L23 Caches IV / VM I (10) Garcia, Spring 2004 © UCB Big Idea How to choose between associativity, block size, replacement policy? Design against a performance model Minimize: Average Memory Access Time = Hit Time + Miss Penalty x Miss Rate influenced by technology & program behavior Note: Hit Time encompasses Hit Rate!!! Create the illusion of a memory that is large, cheap, and fast - on average

CS 61C L23 Caches IV / VM I (11) Garcia, Spring 2004 © UCB Example Assume Hit Time = 1 cycle Miss rate = 5% Miss penalty = 20 cycles Calculate AMAT… Avg mem access time = x 20 = cycles = 2 cycles

CS 61C L23 Caches IV / VM I (12) Garcia, Spring 2004 © UCB Upcoming Calendar Week #MonWedThurs LabFri #9 This week Dan Caches IV / VM I Dan VM II Caches No Dan OH Chema VM III #9+ Sp Break! It’sPartyTime Woo Hoo! Who has the most exciting spring break plans?

CS 61C L23 Caches IV / VM I (13) Garcia, Spring 2004 © UCB But more important than anything… March Madness Baby!

CS 61C L23 Caches IV / VM I (14) Garcia, Spring 2004 © UCB Administrivia Midterm You have until Friday to ask for regrade Staple explanation to cover, submit to TA

CS 61C L23 Caches IV / VM I (15) Garcia, Spring 2004 © UCB Ways to reduce miss rate Larger cache limited by cost and technology hit time of first level cache < cycle time More places in the cache to put each block of memory – associativity fully-associative -any block any line k-way set associated -k places for each block -direct map: k=1

CS 61C L23 Caches IV / VM I (16) Garcia, Spring 2004 © UCB Improving Miss Penalty When caches first became popular, Miss Penalty ~ 10 processor clock cycles Today 2400 MHz Processor (0.4 ns per clock cycle) and 80 ns to go to DRAM  200 processor clock cycles! Proc $2$2 DRAM $ MEM Solution: another cache between memory and the processor cache: Second Level (L2) Cache

CS 61C L23 Caches IV / VM I (17) Garcia, Spring 2004 © UCB Analyzing Multi-level cache hierarchy Proc $2$2 DRAM $ L1 hit time L1 Miss Rate L1 Miss Penalty Avg Mem Access Time = L1 Hit Time + L1 Miss Rate * L1 Miss Penalty L1 Miss Penalty = L2 Hit Time + L2 Miss Rate * L2 Miss Penalty Avg Mem Access Time = L1 Hit Time + L1 Miss Rate * (L2 Hit Time + L2 Miss Rate * L2 Miss Penalty ) L2 hit time L2 Miss Rate L2 Miss Penalty

CS 61C L23 Caches IV / VM I (18) Garcia, Spring 2004 © UCB Typical Scale L1 size: tens of KB hit time: complete in one clock cycle miss rates: 1-5% L2: size: hundreds of KB hit time: few clock cycles miss rates: 10-20% L2 miss rate is fraction of L1 misses that also miss in L2 why so high?

CS 61C L23 Caches IV / VM I (19) Garcia, Spring 2004 © UCB Example: with L2 cache Assume L1 Hit Time = 1 cycle L1 Miss rate = 5% L2 Hit Time = 5 cycles L2 Miss rate = 15% (% L1 misses that miss) L2 Miss Penalty = 200 cycles L1 miss penalty = * 200 = 35 Avg mem access time = x 35 = 2.75 cycles

CS 61C L23 Caches IV / VM I (20) Garcia, Spring 2004 © UCB Example: without L2 cache Assume L1 Hit Time = 1 cycle L1 Miss rate = 5% L1 Miss Penalty = 200 cycles Avg mem access time = x 200 = 11 cycles 4x faster with L2 cache! (2.75 vs. 11)

CS 61C L23 Caches IV / VM I (21) Garcia, Spring 2004 © UCB What to do on a write hit? Write-through update the word in cache block and corresponding word in memory Write-back update word in cache block allow memory word to be “stale”  add ‘dirty’ bit to each block indicating that memory needs to be updated when block is replaced  OS flushes cache before I/O… Performance trade-offs?

CS 61C L23 Caches IV / VM I (22) Garcia, Spring 2004 © UCB Generalized Caching We’ve discussed memory caching in detail. Caching in general shows up over and over in computer systems Filesystem cache Web page cache Game Theory databases / tablebases Software memoization Others? Big idea: if something is expensive but we want to do it repeatedly, do it once and cache the result.

CS 61C L23 Caches IV / VM I (23) Garcia, Spring 2004 © UCB Another View of the Memory Hierarchy Regs L2 Cache Memory Disk Tape Instr. Operands Blocks Pages Files Upper Level Lower Level Faster Larger Cache Blocks Thus far { { Next: Virtual Memory

CS 61C L23 Caches IV / VM I (24) Garcia, Spring 2004 © UCB Memory Hierarchy Requirements If Principle of Locality allows caches to offer (close to) speed of cache memory with size of DRAM memory, then recursively why not use at next level to give speed of DRAM memory, size of Disk memory? While we’re at it, what other things do we need from our memory system?

CS 61C L23 Caches IV / VM I (25) Garcia, Spring 2004 © UCB Memory Hierarchy Requirements Share memory between multiple processes but still provide protection – don’t let one program read/write memory from another Address space – give each program the illusion that it has its own private memory Suppose code starts at address 0x But different processes have different code, both residing at the same address. So each program has a different view of memory.

CS 61C L23 Caches IV / VM I (26) Garcia, Spring 2004 © UCB Virtual Memory Called “Virtual Memory” Also allows OS to share memory, protect programs from each other Today, more important for protection vs. just another level of memory hierarchy Historically, it predates caches

CS 61C L23 Caches IV / VM I (27) Garcia, Spring 2004 © UCB Peer Instructions 1. Increased associativity  decreased or steady miss rate. 2. Increased associativity  increased cost & slower access time. 3. The ratio of cost of “miss” vs “hit”, VM & cache are within order of mag. ABC 1: FFF 2: FFT 3: FTF 4: FTT 5: TFF 6: TFT 7: TTF 8: TTT

CS 61C L23 Caches IV / VM I (28) Garcia, Spring 2004 © UCB And in Conclusion… Cache design choices: size of cache: speed v. capacity direct-mapped v. associative for N-way set assoc: choice of N block replacement policy 2nd level cache? Write through v. write back? Use performance model to pick between choices, depending on programs, technology, budget,... Virtual Memory Predates caches; each process thinks it has all the memory to itself; protection!