UC Berkeley CS61C : Machine Structures

Similar documents
UC Berkeley CS61C : Machine Structures

UCB CS61C : Machine Structures

CS61C : Machine Structures

! CS61C : Machine Structures. Lecture 22 Caches I. !!Instructor Paul Pearce! ITʼS NOW LEGAL TO JAILBREAK YOUR PHONE!

UCB CS61C : Machine Structures

CS61C : Machine Structures

CS61C : Machine Structures

Review : Pipelining. Memory Hierarchy

CS61C : Machine Structures

CS61C : Machine Structures

CS61C - Machine Structures. Lecture 17 - Caches, Part I. October 25, 2000 David Patterson

Direct-Mapped Cache Terminology. Caching Terminology. TIO Dan s great cache mnemonic. Accessing data in a direct mapped cache

CS61C : Machine Structures

Lctures 33: Cache Memory - I. Some of the slides are adopted from David Patterson (UCB)

UCB CS61C : Machine Structures

CS61C : Machine Structures

CS61C : Machine Structures

Review: New-School Machine Structures. Review: Direct-Mapped Cache. TIO Dan s great cache mnemonic. Memory Access without Cache

UC Berkeley CS61C : Machine Structures

Lecture 33 Caches III What to do on a write hit? Block Size Tradeoff (1/3) Benefits of Larger Block Size

CS61C : Machine Structures

CS61C : Machine Structures

Review: Performance Latency vs. Throughput. Time (seconds/program) is performance measure Instructions Clock cycles Seconds.

UC Berkeley CS61C : Machine Structures

UCB CS61C : Machine Structures

CS61C : Machine Structures

Block Size Tradeoff (1/3) Benefits of Larger Block Size. Lecture #22 Caches II Block Size Tradeoff (3/3) Block Size Tradeoff (2/3)

CS 61C: Great Ideas in Computer Architecture. Direct Mapped Caches

www-inst.eecs.berkeley.edu/~cs61c/

CMPT 300 Introduction to Operating Systems

CS61C : Machine Structures

Chapter 2: Memory Hierarchy Design, part 1 - Introducation. Advanced Computer Architecture Mehran Rezaei

Clever Signed Adder/Subtractor. Five Components of a Computer. The CPU. Stages of the Datapath (1/5) Stages of the Datapath : Overview

Memory Hierarchy, Fully Associative Caches. Instructor: Nick Riasanovsky

Memory Hierarchy. Mehran Rezaei

CS61C : Machine Structures

UC Berkeley CS61C : Machine Structures

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Caches Part 1

Cache Memory - II. Some of the slides are adopted from David Patterson (UCB)

CS 61C: Great Ideas in Computer Architecture. The Memory Hierarchy, Fully Associative Caches

CS61C : Machine Structures

Another View of the Memory Hierarchy. Lecture #25 Virtual Memory I Memory Hierarchy Requirements. Memory Hierarchy Requirements

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Caches Part 1

10/11/17. New-School Machine Structures. Review: Single Cycle Instruction Timing. Review: Single-Cycle RISC-V RV32I Datapath. Components of a Computer

CSF Cache Introduction. [Adapted from Computer Organization and Design, Patterson & Hennessy, 2005]

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Lecture 36: IO Basics

CPU Pipelining Issues

UCB CS61C : Machine Structures

Lecture 17 Introduction to Memory Hierarchies" Why it s important " Fundamental lesson(s)" Suggested reading:" (HP Chapter

14:332:331. Week 13 Basics of Cache

Caches Part 1. Instructor: Sören Schwertfeger. School of Information Science and Technology SIST

And in Review! ! Locality of reference is a Big Idea! 3. Load Word from 0x !

Review. Motivation for Input/Output. What do we need to make I/O work?

UC Berkeley CS61C : Machine Structures

Welcome to Part 3: Memory Systems and I/O

Final Exam Fall 2008

CS 61C: Great Ideas in Computer Architecture. Multiple Instruction Issue, Virtual Memory Introduction

Question?! Processor comparison!

EEC 170 Computer Architecture Fall Cache Introduction Review. Review: The Memory Hierarchy. The Memory Hierarchy: Why Does it Work?

Donn Morrison Department of Computer Science. TDT4255 Memory hierarchies

CS61C : Machine Structures

CPE 631 Lecture 04: CPU Caches

Let!s go back to a course goal... Let!s go back to a course goal... Question? Lecture 22 Introduction to Memory Hierarchies

UCB CS61C : Machine Structures

ENGN 2910A Homework 03 (140 points) Due Date: Oct 3rd 2013

Levels in memory hierarchy

Textbook: Burdea and Coiffet, Virtual Reality Technology, 2 nd Edition, Wiley, Textbook web site:

Administrivia. CMSC 411 Computer Systems Architecture Lecture 8 Basic Pipelining, cont., & Memory Hierarchy. SPEC92 benchmarks

CS 61C: Great Ideas in Computer Architecture Direct- Mapped Caches. Increasing distance from processor, decreasing speed.

Lecture #6 Intro MIPS; Load & Store

Multi-cycle Instructions in the Pipeline (Floating Point)

CS61C : Machine Structures

CISC 662 Graduate Computer Architecture Lecture 16 - Cache and virtual memory review

LECTURE 11. Memory Hierarchy

1" 0" d" c" b" a" ...! ! Benefits of Larger Block Size. " Very applicable with Stored-Program Concept " Works well for sequential array accesses

3/12/2014. Single Cycle (Review) CSE 2021: Computer Organization. Single Cycle with Jump. Multi-Cycle Implementation. Why Multi-Cycle?

Memory Hierarchy. ENG3380 Computer Organization and Architecture Cache Memory Part II. Topics. References. Memory Hierarchy

CS61C : Machine Structures

Memory. Lecture 22 CS301

61C In the News. Review. Memory Management Today. Impact of Paging on AMAT

Advanced Memory Organizations

Memory Hierarchy: Motivation

ECE468 Computer Organization and Architecture. Memory Hierarchy

Modern Computer Architecture

CS161 Design and Architecture of Computer Systems. Cache $$$$$

CS61C : Machine Structures

CS61C : Machine Structures

Pipelining. CSC Friday, November 6, 2015

CS61C : Machine Structures

The Processor: Instruction-Level Parallelism

UC Berkeley CS61C : Machine Structures

c. What are the machine cycle times (in nanoseconds) of the non-pipelined and the pipelined implementations?

Performance! (1/latency)! 1000! 100! 10! Capacity Access Time Cost. CPU Registers 100s Bytes <10s ns. Cache K Bytes ns 1-0.

CS 61C: Great Ideas in Computer Architecture. Virtual Memory

Page 1. Multilevel Memories (Improving performance using a little cash )

Computer Architecture Spring 2016

Memory Hierarchy Motivation, Definitions, Four Questions about Memory Hierarchy

Memory Hierarchy Technology. The Big Picture: Where are We Now? The Five Classic Components of a Computer

CS 61C: Great Ideas in Computer Architecture (Machine Structures) Caches Part 2

EE 4683/5683: COMPUTER ARCHITECTURE

Transcription:

inst.eecs.berkeley.edu/~cs61c UC Berkeley CS61C : Machine Structures Lecture 31 Caches I 2007-04-06 Powerpoint bad!! Research done at the Univ of NSW says that working memory, the brain part providing temporary storage, is limited (3-4 things for 20 sec unless rehearsal), and saying what is on slides splits attention, & bad. CS61C L31 Caches I (1) Lecturer SOE Dan Garcia www.cs.berkeley.edu/~ddgarcia slashdot.org/article.pl?sid=07/04/04/1319247

Review : Pipelining Pipeline challenge is hazards Forwarding helps w/many data hazards Delayed branch helps with control hazard in our 5 stage pipeline Data hazards w/loads Load Delay Slot Interlock smart CPU has HW to detect if conflict with inst following load, if so it stalls More aggressive performance (discussed in section next week) Superscalar (parallelism) Out-of-order execution CS61C L31 Caches I (2)

Peer Instruction (2/2) Assume 1 instr/clock, delayed branch, 5 stage pipeline, forwarding, interlock on unresolved load hazards (after 10 3 loops, so pipeline full). Rewrite this code to reduce pipeline stages (clock cycles) per loop to as few as possible. Loop: lw $t0, 0($s1) addu $t0, $t0, $s2 sw $t0, 0($s1) addiu $s1, $s1, -4 bne $s1, $zero, Loop nop How many pipeline stages (clock cycles) per loop iteration to execute this code? Thanks to Peter Devore for catching this! addiu $s1,$s1,-4 bne $s1, $0, Loop CS61C L31 Caches I (3) IF ID/RF EX MEM WB ALU I$ Reg D$ Reg? I$ Reg D$ Reg ALU Patterson: Real HW has this forwarding (no stall), but for simplicity, COD doesn t (stall) - p. 419.

The Big Picture Computer Processor (active) Control ( brain ) Datapath ( brawn ) Memory (passive) (where programs, data live when running) Devices Input Output Keyboard, Mouse Disk, Network Display, Printer CS61C L31 Caches I (4)

Memory Hierarchy Storage in computer systems: Processor holds data in register file (~100 Bytes) Registers accessed on nanosecond timescale Memory (we ll call main memory ) Disk More capacity than registers (~Gbytes) Access time ~50-100 ns Hundreds of clock cycles per memory access?! HUGE capacity (virtually limitless) VERY slow: runs ~milliseconds CS61C L31 Caches I (5)

Motivation: Why We Use Caches (written $) Performance 1000 100 10 1 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 CPU DRAM µproc 60%/yr. Processor-Memory Performance Gap: (grows 50% / year) DRAM 7%/yr. 1989 first Intel CPU with cache on chip 1998 Pentium III has two levels of cache on chip CS61C L31 Caches I (6)

Memory Caching Mismatch between processor and memory speeds leads us to add a new level: a memory cache Implemented with same IC processing technology as the CPU (usually integrated on same chip): faster but more expensive than DRAM memory. Cache is a copy of a subset of main memory. Most processors have separate caches for instructions and data. CS61C L31 Caches I (7)

Memory Hierarchy Processor Higher Levels in memory hierarchy Lower Level 1 Level 2 Level 3... Level n Increasing Distance from Proc., Decreasing speed Size of memory at each level As we move to deeper levels the latency goes up and price per bit goes down. CS61C L31 Caches I (8)

Memory Hierarchy If level closer to Processor, it is: smaller faster subset of lower levels (contains most recently used data) Lowest Level (usually disk) contains all available data (or does it go beyond the disk?) Memory Hierarchy presents the processor with the illusion of a very large very fast memory. CS61C L31 Caches I (9)

Memory Hierarchy Analogy: Library (1/2) You re writing a term paper (Processor) at a table in Doe Doe Library is equivalent to disk essentially limitless capacity very slow to retrieve a book Table is main memory smaller capacity: means you must return book when table fills up easier and faster to find a book there once you ve already retrieved it CS61C L31 Caches I (10)

Memory Hierarchy Analogy: Library (2/2) Open books on table are cache smaller capacity: can have very few open books fit on table; again, when table fills up, you must close a book much, much faster to retrieve data Illusion created: whole library open on the tabletop Keep as many recently used books open on table as possible since likely to use again Also keep as many books on table as possible, since faster than going to library CS61C L31 Caches I (11)

Memory Hierarchy Basis Cache contains copies of data in memory that are being used. Memory contains copies of data on disk that are being used. Caches work on the principles of temporal and spatial locality. Temporal Locality: if we use it now, chances are we ll want to use it again soon. Spatial Locality: if we use a piece of memory, chances are we ll use the neighboring pieces soon. CS61C L31 Caches I (12)

Cache Design How do we organize cache? Where does each memory address map to? (Remember that cache is subset of memory, so multiple memory addresses map to the same cache location.) How do we know which elements are in cache? How do we quickly locate them? CS61C L31 Caches I (13)

Administrivia Project 4 (on Caches) will be in optional groups of two. I m releasing old CS61C finals Check the course web page CS61C L31 Caches I (14)

Direct-Mapped Cache (1/4) In a direct-mapped cache, each memory address is associated with one possible block within the cache Therefore, we only need to look in a single location in the cache for the data if it exists in the cache Block is the unit of transfer between cache and memory CS61C L31 Caches I (15)

Memory Address 0 12 Direct-Mapped Cache (2/4) 3 4 5 6 7 8 9 A B C D E F Memory CS61C L31 Caches I (16) Cache Index 0 1 2 3 4 Byte Direct Mapped Cache Block size = 1 byte Cache Location 0 can be occupied by data from: Memory location 0, 4, 8,... 4 blocks any memory location that is multiple of 4 What if we wanted a block to be bigger than one byte?

Memory Address 0 24 6 8 A C E 10 12 14 16 18 1A 1C 1E Direct-Mapped Cache (3/4) Memory 1 3 5 7 9 0 2 4 6 8 etc CS61C L31 Caches I (17) Cache Index 0 1 2 3 8 Byte Direct Mapped Cache Block size = 2 bytes When we ask for a byte, the system finds out the right block, and loads it all! How does it know right block? How do we select the byte? E.g., Mem address 11101? How does it know WHICH colored block it originated from? What do you do at baggage claim?

Direct-Mapped Cache (4/4) 0 24 6 8 A C E 10 12 14 16 18 1A 1C 1E Memory Address Memory (addresses shown) 1 3 5 7 9 0 2 4 6 8 etc CS61C L31 Caches I (18) 0 1 2 3 Cache Index 0 1 2 3 8 Byte Direct Mapped Cache w/tag! 8 0 3 1E 14 0 2 3 Tag Data (Block size = 2 bytes) What should go in the tag? Do we need the entire address? What do all these tags have in common? What did we do with the immediate when we were branch addressing, always count by bytes? Why not count by cache #? Cache# It s useful to draw memory with the same width as the block size

Issues with Direct-Mapped Since multiple memory addresses map to same cache index, how do we tell which one is in there? What if we have a block size > 1 byte? Answer: divide memory address into three fields ttttttttttttttttt iiiiiiiiii oooo tag index byte to check to offset if have select within correct block block block CS61C L31 Caches I (19)

Direct-Mapped Cache Terminology All fields are read as unsigned integers. Index: specifies the cache index (which row /block of the cache we should look in) Offset: once we ve found correct block, specifies which byte within the block we want Tag: the remaining bits after offset and index are determined; these are used to distinguish between all the memory addresses that map to the same location CS61C L31 Caches I (20)

TIO Dan s great cache mnemonic AREA (cache size, B) 2 (H+W) = 2 H * 2 W = HEIGHT (# of blocks) * WIDTH (size of one block, B/block) Tag Index Offset WIDTH (size of one block, B/block) HEIGHT (# of blocks) AREA (cache size, B) CS61C L31 Caches I (21)

Direct-Mapped Cache Example (1/3) Suppose we have a 16KB of data in a direct-mapped cache with 4 word blocks Determine the size of the tag, index and offset fields if we re using a 32-bit architecture Offset need to specify correct byte within a block block contains 4 words = 16 bytes = 2 4 bytes need 4 bits to specify correct byte CS61C L31 Caches I (22)

Direct-Mapped Cache Example (2/3) Index: (~index into an array of blocks ) need to specify correct block in cache cache contains 16 KB = 2 14 bytes block contains 2 4 bytes (4 words) # blocks/cache = bytes/cache bytes/block = 2 14 bytes/cache 2 4 bytes/block = 2 10 blocks/cache need 10 bits to specify this many blocks CS61C L31 Caches I (23)

Direct-Mapped Cache Example (3/3) Tag: use remaining bits as tag tag length = addr length offset - index = 32-4 - 10 bits = 18 bits so tag is leftmost 18 bits of memory address Why not full 32 bit address as tag? All bytes within block need same address (4b) Index must be same for every address within a block, so it s redundant in tag check, thus can leave off to save memory (here 10 bits) CS61C L31 Caches I (24)

Peer Instruction A. Mem hierarchies were invented before 1950. (UNIVAC I wasn t delivered til 1951) B. If you know your computer s cache size, you can often make your code run faster. C. Memory hierarchies take advantage of spatial locality by keeping the most recent data items closer to the processor. CS61C L31 Caches I (25) ABC 0: FFF 1: FFT 2: FTF 3: FTT 4: TFF 5: TFT 6: TTF 7: TTT

Peer Instruction (2/2) Assume 1 instr/clock, delayed branch, 5 stage pipeline, forwarding, interlock on unresolved load hazards (after 10 3 loops, so pipeline full). Rewrite this code to reduce pipeline stages (clock cycles) per loop to as few as possible. Loop: lw $t0, 0($s1) addu $t0, $t0, $s2 sw $t0, 0($s1) addiu $s1, $s1, -4 bne $s1, $zero, Loop nop How many pipeline stages (clock cycles) per loop iteration to execute this code? CS61C L31 Caches I (27) 1 2 3 4 5 6 7 8 9 10

And in Conclusion We would like to have the capacity of disk at the speed of the processor: unfortunately this is not feasible. So we create a memory hierarchy: each successively lower level contains most used data from next higher level exploits temporal & spatial locality do the common case fast, worry less about the exceptions (design principle of MIPS) Locality of reference is a Big Idea CS61C L31 Caches I (29)