Instructors: Randy H. Katz David A. PaGerson hgp://inst.eecs.berkeley.edu/~cs61c/fa10. Fall Lecture #39. Agenda

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1 2/2/ CS 6C: Great Ideas in Computer Architecture (Machine Structures) Project 3 Speed- up and RAID Instructors: Randy H Katz David A PaGerson hgp://insteecsberkeleyedu/~cs6c/fa 2// Fall Lecture #39 Agenda Programming Project Results Administrivia Technology Break RAID 2// Fall Lecture #39 2

2 2/2/ Agenda Programming Project Results Administrivia Technology Break RAID 2// Fall Lecture #39 3 Project #3, Part I sgemm (x5) 3 levels blocking, loop unrolling MFlop/s Class Data Peak Simple Blocked Thanks TA Andrew! 2// Fall Lecture #3 4 2

3 2/2/ Project #3, Part I Num Submissions sgemm (x5) Performance Histogram MFlop/s Thanks TA Andrew! 2// Fall Lecture #3 5 No SSE sgemm (x5) 3 levels blocking, loop unrolling MFlop/s // Fall Lecture #39 6 3

4 2/2/ No SSE sgemm (x5, Peak: 475) 3 levels blocking, loop unrolling % peak // Fall Lecture #39 7 No SSE 35 3 sgemm (x5) Performance Histogram Num Submissions MFlop/s 2// Fall Lecture #39 8 4

5 2/2/ SSE Gflop/s sgemm SSE ( thread) A = x5 A'A Simple Blocked GotoBLAS2 CS6c 2// Fall Lecture #39 9 SSE % of Goto Single-thread x5 A'A 8 7 % Goto (74 Gflop/s) // Fall Lecture #39 5

6 2/2/ SSE Histogram of Performance (SSE) A = x5 2 # submissions Gflop/s 2// Fall Lecture #39 OMP 4 sgemm OMP (8 threads,a'a) A = x5 2 Gflop/s Naive GotoBLAS2 CS6c 2 2// Fall Lecture #39 2 6

7 2/2/ OMP 9 % of Goto OMP (8 threads) x5 8 % Goto (22 Gflop/s) // Fall Lecture #39 3 OMP # submissions Histogram of performance (OMP) A = x Gflop/s 2// Fall Lecture #39 4 7

8 2/2/ 35 Extra Credit EC and Part 2 (serial) A'A (x5) Gflop/s 5 EC Part 2 5 2// Fall Lecture #39 5 Extra Credit 25 EC and Part 2 (8 threads) A'A (x5) 2 Gflop/s 5 EC Part 2 5 2// Fall Lecture #39 6 8

9 2/2/ Extra Credit 3 Performance Change (serial) A'A (x5) 25 Speedup (EC/Part2) // Fall Lecture #39 7 Extra Credit Performance Change (8 threads) A'A (x5) 3 25 Speedup (EC/Part2) // Fall Lecture #39 8 9

10 2/2/ Agenda Programming Project Results Administrivia Technology Break RAID 2// Fall Lecture #39 9 Administrivia Final Review: Mon Dec 6, 2-5 PM, Evans Final: Mon Dec 3 8- AM (22 Hearst Gym) Like midterm: T/F, M/C, short answers Whole Course: readings, lectures, projects, labs, hw Emphasize 2 nd half of 6C + midterm mistakes 2// Fall Lecture #39 2

11 2/2/ Cloud Compucng Administrivia Technology Break Datacenter Economics Agenda 2// Fall Lecture #39 2 Agenda Programming Project Results Administrivia Technology Break RAID 2// Fall Lecture #39 22

12 2/2/ Evolucon of the Disk Drive IBM 339K, 986 IBM RAMAC 35, 956 Apple SCSI, 986 2// Fall Lecture #39 23 Arrays of Small Disks Can smaller disks be used to close gap in performance between disks and CPUs? Convenconal: 4 disk designs Low End 4 High End Disk Array: disk design 35 2// Fall Lecture #

13 2/2/ Replace Small Number of Large Disks with Large Number of Small Disks! (988 Disks) IBM 339K IBM 35" 6 x7 2 GBytes 32 MBytes 23 GBytes Capacity Volume Power Data Rate I/O Rate MTTF Cost 97 cu i 3 KW 5 MB/s 6 I/Os/s 25 KHrs $25K cu i W 5 MB/s 55 I/Os/s 5 KHrs $2K cu i KW 2 MB/s 39 IOs/s??? Hrs $5K Disk Arrays have potencal for large data and I/O rates, high MB per cu i, high MB per KW, but what about reliability? 2// Fall Lecture # X 3X 8X 6X RAID: Redundant Arrays of (Inexpensive) Disks Files are "striped" across mulcple disks Redundancy yields high data availability Availability: service scll provided to user, even if some components failed Disks will scll fail Contents reconstructed from data redundantly stored in the array Capacity penalty to store redundant info Bandwidth penalty to update redundant info 2// Fall Lecture #

14 2/2/ Redundant Arrays of Inexpensive Disks RAID : Disk Mirroring/Shadowing recovery group Each disk is fully duplicated onto its mirror Very high availability can be achieved Bandwidth sacrifice on write: Logical write = two physical writes Reads may be opcmized Most expensive solucon: % capacity overhead 2// Fall Lecture #39 27 Redundant Array of Inexpensive Disks RAID 3: Parity Disk logical record Striped physical records P contains sum of other disks per stripe mod 2 ( parity ) If disk fails, subtract P from sum of other disks to find missing informacon 2// Fall Lecture #39 28 P 4

15 2/2/ Redundant Arrays of Inexpensive Disks RAID 4: High I/O Rate Parity Insides of 5 disks Example: small read D & D5, large write D2- D5 D D D2 D3 P D4 D5 D6 D7 P D8 D9 D D P D2 D3 D4 D5 D6 D7 D8 D9 D2 D2 D22 D23 P Disk Columns P P Increasing Logical Disk Address Stripe 2// Fall Lecture #39 29 Inspiracon for RAID 5 RAID 4 works well for small reads Small writes (write to one disk): Opcon : read other data disks, create new sum and write to Parity Disk Opcon 2: since P has old sum, compare old data to new data, add the difference to P Small writes are limited by Parity Disk: Write to D, D5 both also write to P disk D D D2 D3 P D4 D5 D6 D7 P 2// Fall Lecture #39 3 5

16 2/2/ RAID 5: High I/O Rate Interleaved Parity Independent writes possible because of interleaved parity D D D2 D3 P D4 D5 D6 P D7 D8 D9 P D D D2 P D3 D4 D5 Increasing Logical Disk Addresses Example: write to D, D5 uses disks,, 3, 4 P D6 D7 D8 D9 D2 D2 D22 D23 P Disk Columns 2// Fall Lecture #39 3 Problems of Disk Arrays: Small Writes RAID- 5: Small Write Algorithm Logical Write = 2 Physical Reads + 2 Physical Writes D' D D D2 D3 P new data + old data XOR ( Read) old parity (2 Read) + XOR (3 Write) (4 Write) D' D D2 D3 P' 2// Fall Lecture #

17 2/2/ Tech Report Read Round the World (December 987) 2// Fall Lecture #39 33 RAID- I RAID- I (989) Consisted of a Sun 4/28 workstacon with 28 MB of DRAM, four dual- string SCSI controllers, inch SCSI disks and specialized disk striping soiware 2// Fall Lecture #

18 2/2/ RAID II Early Network AGached Storage (NAS) System running a Log Structured File System (LFS) Impact: $25 Billion/year in 22 Over $5 Billion in RAID device sold since RAID companies (at the peak) Soiware RAID a standard component of modern OSs 2// Fall Lecture #39 35 RAID II 2// Fall Lecture #

19 2/2/ Summary Logical- to- physical block mapping, parity striping, read- modify- write processing Embedded caches and orchestracng data staging between network interfaces, parity hardware, and file server interfaces Failed disk replacement, hot spares, background copies and backup Embedded log- structured file systems, compression on the fly Soiware complexity dominates hardware! 2// Fall Lecture #