Tunning aix

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Tunning aix

  1. 1. Front coverAIX 5L PracticalPerformance Toolsand Tuning GuideUpdated performance information forIBM Eserver p5 and AIX 5L V5.3New tools for Eserver p5 withSMT and Micro-PartitioningPractical performance problemdetermination examples Kumiko Hayashi Kangkook Ji Octavian Lascu Hennie Pienaar Susan Schreitmueller Tina Tarquinio James Thompsonibm.com/redbooks
  2. 2. International Technical Support OrganizationAIX 5L Practical Performance Tools and TuningGuideApril 2005 SG24-6478-00
  3. 3. Note: Before using this information and the product it supports, read the information in “Notices” on page ix.First Edition (April 2005)This edition applies to Version 5, Release 3, of AIX 5L (product number 5765-G03).© Copyright International Business Machines Corporation 2005. All rights reserved.Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADPSchedule Contract with IBM Corp.
  4. 4. Contents Notices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Trademarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi The team that wrote this redbook. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi Become a published author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii Comments welcome. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xivPart 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 1. Performance overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1 Performance expectations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.1.1 System workload. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.1.2 Performance objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.1.3 Program execution model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.1.4 System tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 1.2 Introduction to the performance tuning process . . . . . . . . . . . . . . . . . . . . 13 1.2.1 Performance management phases . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Chapter 2. Performance analysis and tuning . . . . . . . . . . . . . . . . . . . . . . . 21 2.1 CPU performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.1.1 Processes and threads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.1.2 SMP performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.1.3 Initial advice for monitoring CPU . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.2 Memory overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.2.1 Virtual memory manager (VMM) overview . . . . . . . . . . . . . . . . . . . . 32 2.2.2 Paging space overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2.3 Disk I/O performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.3.1 Initial advice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.3.2 Disk subsystem design approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.3.3 Bandwidth-related performance considerations . . . . . . . . . . . . . . . . 38 2.3.4 Disk design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.3.5 Logical Volume Manager concepts . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.4 Network performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 2.4.1 Initial advice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 2.4.2 TCP/IP protocol. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 2.4.3 Network tunables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Part 2. Performance tools. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61© Copyright IBM Corp. 2005. All rights reserved. iii
  5. 5. Chapter 3. General performance monitoring tools . . . . . . . . . . . . . . . . . . 63 3.1 The topas command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.1.1 Topas syntax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3.1.2 Basic topas output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 3.1.3 Partition statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.2 The jtopas utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 3.2.1 The jtopas configuration file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 3.2.2 The info section for the jtopas tool . . . . . . . . . . . . . . . . . . . . . . . . . . 74 3.2.3 The jtopas consoles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 3.2.4 The jtopas playback tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 3.3 The perfpmr utility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 3.3.1 Information about measurement and sampling . . . . . . . . . . . . . . . . . 78 3.3.2 Building and submitting a test case. . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.3.3 Examples for perfpmr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 3.4 Performance Diagnostic Tool (PDT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 3.4.1 Examples for PDT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 3.4.2 Using reports generated by PDT. . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 3.4.3 Running PDT collection manually . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 3.5 The curt command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 3.5.1 Information about measurement and sampling . . . . . . . . . . . . . . . . . 96 3.5.2 Examples for curt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 3.5.3 Overview of the reports generated by curt . . . . . . . . . . . . . . . . . . . . 99 3.5.4 The default report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 3.6 The splat command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 3.6.1 splat syntax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 3.6.2 Information about measurement and sampling . . . . . . . . . . . . . . . . 122 3.6.3 The execution, trace, and analysis intervals . . . . . . . . . . . . . . . . . . 123 3.6.4 Trace discontinuities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 3.6.5 Address-to-name resolution in splat . . . . . . . . . . . . . . . . . . . . . . . . 124 3.6.6 splat examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 3.7 The trace, trcnm, and trcrpt commands . . . . . . . . . . . . . . . . . . . . . . . . . 147 3.7.1 The trace command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 3.7.2 Information about measurement and sampling . . . . . . . . . . . . . . . . 152 3.7.3 How to start and stop trace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 3.7.4 Running trace interactively . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 3.7.5 Running trace asynchronously . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 3.7.6 Running trace on an entire system for 10 seconds . . . . . . . . . . . . . 157 3.7.7 Tracing a command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 3.7.8 Tracing using one set of buffers per CPU . . . . . . . . . . . . . . . . . . . . 158 3.7.9 Examples for trace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 3.7.10 The trcnm command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 3.7.11 Examples for trcnm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 3.7.12 The trcrpt command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165iv AIX 5L Practical Performance Tools and Tuning Guide
  6. 6. 3.7.13 Examples for trcrpt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169Chapter 4. CPU analysis and tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1714.1 CPU overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.1.1 Performance considerations with POWER4-based systems . . . . . 172 4.1.2 Performance considerations with POWER5-based systems . . . . . 1724.2 CPU monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 4.2.1 The lparstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174 4.2.2 The mpstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 4.2.3 The procmon tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 4.2.4 The topas command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 4.2.5 The sar command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 4.2.6 The iostat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 4.2.7 The vmstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208 4.2.8 The ps command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 4.2.9 The trace tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 4.2.10 The curt command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 4.2.11 The splat command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 4.2.12 The truss command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 4.2.13 The gprof command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 4.2.14 The pprof command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 262 4.2.15 The prof command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 4.2.16 The tprof command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 270 4.2.17 The time command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 4.2.18 The timex command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2734.3 CPU related tuning tools and techniques . . . . . . . . . . . . . . . . . . . . . . . . 276 4.3.1 The smtctl command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276 4.3.2 The bindintcpu command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278 4.3.3 The bindprocessor command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280 4.3.4 The schedo command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 4.3.5 The nice command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288 4.3.6 The renice command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2894.4 CPU summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 4.4.1 Other useful commands for CPU monitoring . . . . . . . . . . . . . . . . . 291Chapter 5. Memory analysis and tuning . . . . . . . . . . . . . . . . . . . . . . . . . . 2975.1 Memory monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 5.1.1 The ps command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 5.1.2 The sar command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 300 5.1.3 The svmon command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 5.1.4 The topas monitoring tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 5.1.5 The vmstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3105.2 Memory tuning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 Contents v
  7. 7. 5.2.1 The vmo command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 5.2.2 Paging space thresholds tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 5.3 Memory summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 5.3.1 Other useful commands for memory performance . . . . . . . . . . . . . 330 5.3.2 Paging space commands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 Chapter 6. Network performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 6.1 Network overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334 6.1.1 The maxmbuf tunable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336 6.2 Hardware considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340 6.2.1 Firmware levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340 6.2.2 Media speed considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 6.2.3 MTU size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 342 6.3 Network monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 6.3.1 Creating network load . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 349 6.4 Network monitoring commands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351 6.4.1 The entstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351 6.4.2 The netstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356 6.4.3 The pmtu command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 370 6.5 Network packet tracing tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 6.5.1 The iptrace command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 6.5.2 The ipreport command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374 6.5.3 The ipfilter command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 6.5.4 The netpmon command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376 6.5.5 The trpt command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384 6.6 NFS related performance commands . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 6.6.1 The nfsstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389 6.7 Network tuning commands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 6.7.1 The no command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 6.7.2 The Interface Specific Network Options (ISNO) . . . . . . . . . . . . . . . 415 6.7.3 The nfso command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 Chapter 7. Storage analysis and tuning . . . . . . . . . . . . . . . . . . . . . . . . . . 425 7.1 Data placement and design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 7.1.1 AIX I/O stack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 7.1.2 Physical disk and disk subsystem . . . . . . . . . . . . . . . . . . . . . . . . . . 428 7.1.3 Device drivers and adapters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429 7.1.4 Volume groups and logical volumes . . . . . . . . . . . . . . . . . . . . . . . . 430 7.1.5 VMM and direct I/O . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431 7.1.6 JFS/JFS2 file systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 432 7.2 Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 7.2.1 The iostat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 7.2.2 The filemon command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441vi AIX 5L Practical Performance Tools and Tuning Guide
  8. 8. 7.2.3 The fileplace command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449 7.2.4 The lslv, lspv, and lsvg commands . . . . . . . . . . . . . . . . . . . . . . . . . 463 7.2.5 The lvmstat command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475 7.2.6 The sar -d command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 478 7.3 Tuning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 7.3.1 The lsdev, rmdev and mkdev commands . . . . . . . . . . . . . . . . . . . . 480 7.3.2 The lscfg, lsattr, and chdev commands. . . . . . . . . . . . . . . . . . . . . . 487 7.3.3 The ioo command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495 7.3.4 The lvmo command. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 499 7.3.5 The vmo command . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500Part 3. Case studies and miscellaneous tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501 Chapter 8. Case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 8.1 Case study: NIM server. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504 8.1.1 Setting up the environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504 8.1.2 Monitoring NIM master using topas . . . . . . . . . . . . . . . . . . . . . . . . 506 8.1.3 Upgrading NIM environment to Gbit Ethernet . . . . . . . . . . . . . . . . . 510 8.1.4 Upgrading the disk storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512 8.1.5 Real workload with spread file system . . . . . . . . . . . . . . . . . . . . . . 520 8.1.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522 8.2 POWER5 case study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523 8.2.1 POWER5 introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523 8.2.2 High CPU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524 8.2.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 Chapter 9. Miscellaneous tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533 9.1 Workload manager monitoring (WLM) . . . . . . . . . . . . . . . . . . . . . . . . . . 534 9.1.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 534 9.1.2 WLM concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535 9.1.3 Administering WLM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537 9.1.4 WLM performance tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 546 9.2 Partition load manager (PLM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549 9.2.1 PLM introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549 9.2.2 Memory management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553 9.2.3 Processor management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553 9.3 A comparison of WLM and PLM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554 9.4 Resource monitoring and control (RMC) . . . . . . . . . . . . . . . . . . . . . . . . . 557 9.4.1 RMC commands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559 9.4.2 Information about measurement and sampling . . . . . . . . . . . . . . . . 560 9.4.3 Verifying RMC facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565 9.4.4 Examples using RMC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 570 Chapter 10. Performance monitoring APIs . . . . . . . . . . . . . . . . . . . . . . . . 583 Contents vii
  9. 9. 10.1 The performance status (Perfstat) API . . . . . . . . . . . . . . . . . . . . . . . . . 584 10.1.1 Compiling and linking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 586 10.1.2 Changing history of perfstat API . . . . . . . . . . . . . . . . . . . . . . . . . . 586 10.1.3 Subroutines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 587 10.2 System Performance Measurement Interface . . . . . . . . . . . . . . . . . . . . 620 10.2.1 Compiling and linking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 621 10.2.2 Terms and concepts for SPMI. . . . . . . . . . . . . . . . . . . . . . . . . . . . 621 10.2.3 Subroutines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624 10.2.4 Basic layout of SPMI program. . . . . . . . . . . . . . . . . . . . . . . . . . . . 629 10.2.5 SPMI examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632 10.3 Performance Monitor API . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 637 10.3.1 Performance Monitor data access . . . . . . . . . . . . . . . . . . . . . . . . 638 10.3.2 Compiling and linking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639 10.3.3 Subroutines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639 10.3.4 PM API examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 640 10.3.5 PMAPI M:N pthreads support . . . . . . . . . . . . . . . . . . . . . . . . . . . . 643 10.4 Miscellaneous performance monitoring subroutines . . . . . . . . . . . . . . . 644 10.4.1 Compiling and linking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 644 10.4.2 Subroutines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 644 10.4.3 Combined example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 662 Appendix A. Source code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665 perfstat_dump_all.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666 perfstat_dude.c. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 670 spmi_dude.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 679 spmi_data.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 683 spmi_file.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 689 Spmi_traverse.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 691 dudestat.c. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 Appendix B. Trace hooks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 699 AIX 5L trace hooks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 700 Abbreviations and acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 709 Related publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 711 IBM Redbooks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 711 Other publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 712 Online resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713 How to get IBM Redbooks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713 Help from IBM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 715viii AIX 5L Practical Performance Tools and Tuning Guide
  10. 10. NoticesThis information was developed for products and services offered in the U.S.A.IBM may not offer the products, services, or features discussed in this document in other countries. Consultyour local IBM representative for information on the products and services currently available in your area.Any reference to an IBM product, program, or service is not intended to state or imply that only that IBMproduct, program, or service may be used. Any functionally equivalent product, program, or service thatdoes not infringe any IBM intellectual property right may be used instead. However, it is the usersresponsibility to evaluate and verify the operation of any non-IBM product, program, or service.IBM may have patents or pending patent applications covering subject matter described in this document.The furnishing of this document does not give you any license to these patents. You can send licenseinquiries, in writing, to:IBM Director of Licensing, IBM Corporation, North Castle Drive Armonk, NY 10504-1785 U.S.A.The following paragraph does not apply to the United Kingdom or any other country where such provisionsare inconsistent with local law: INTERNATIONAL BUSINESS MACHINES CORPORATION PROVIDESTHIS PUBLICATION "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED,INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF NON-INFRINGEMENT,MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Some states do not allow disclaimerof express or implied warranties in certain transactions, therefore, this statement may not apply to you.This information could include technical inaccuracies or typographical errors. Changes are periodically madeto the information herein; these changes will be incorporated in new editions of the publication. IBM maymake improvements and/or changes in the product(s) and/or the program(s) described in this publication atany time without notice.Any references in this information to non-IBM Web sites are provided for convenience only and do not in anymanner serve as an endorsement of those Web sites. The materials at those Web sites are not part of thematerials for this IBM product and use of those Web sites is at your own risk.IBM may use or distribute any of the information you supply in any way it believes appropriate withoutincurring any obligation to you.Information concerning non-IBM products was obtained from the suppliers of those products, their publishedannouncements or other publicly available sources. IBM has not tested those products and cannot confirmthe accuracy of performance, compatibility or any other claims related to non-IBM products. Questions onthe capabilities of non-IBM products should be addressed to the suppliers of those products.This information contains examples of data and reports used in daily business operations. To illustrate themas completely as possible, the examples include the names of individuals, companies, brands, and products.All of these names are fictitious and any similarity to the names and addresses used by an actual businessenterprise is entirely coincidental.COPYRIGHT LICENSE:This information contains sample application programs in source language, which illustrates programmingtechniques on various operating platforms. You may copy, modify, and distribute these sample programs inany form without payment to IBM, for the purposes of developing, using, marketing or distributing applicationprograms conforming to the application programming interface for the operating platform for which thesample programs are written. These examples have not been thoroughly tested under all conditions. IBM,therefore, cannot guarantee or imply reliability, serviceability, or function of these programs. You may copy,modify, and distribute these sample programs in any form without payment to IBM for the purposes ofdeveloping, using, marketing, or distributing application programs conforming to IBMs applicationprogramming interfaces.© Copyright IBM Corp. 2005. All rights reserved. ix
  11. 11. TrademarksThe following terms are trademarks of the International Business Machines Corporation in the United States,other countries, or both: Eserver® Hypervisor™ POWER5™ ibm.com® HACMP™ PTX® pSeries® IBM® Redbooks™ AIX 5L™ Micro-Partitioning™ Redbooks (logo) ™ AIX® Nways® RS/6000® DB2® POWER™ Tivoli® Enterprise Storage Server® POWER3™ ESCON® POWER4™The following terms are trademarks of other companies:Java and all Java-based trademarks and logos are trademarks or registered trademarks of SunMicrosystems, Inc. in the United States, other countries, or both.Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in theUnited States, other countries, or both.UNIX is a registered trademark of The Open Group in the United States and other countries.Linux is a trademark of Linus Torvalds in the United States, other countries, or both.Other company, product, and service names may be trademarks or service marks of others.x AIX 5L Practical Performance Tools and Tuning Guide
  12. 12. Preface This IBM® Redbook takes an insightful look at the performance monitoring and tuning tools that are provided with AIX® 5L™. It discusses the usage of the tools as well as the interpretation of the results by using many examples. This redbook is meant as a practical guide for system administrators and AIX technical support professionals so they can use the performance tools in an efficient manner and interpret the outputs when analyzing an AIX system’s performance. This book provides updated information about monitoring and tuning systems performance in an IBM Eserver® POWER5™ and AIX 5L V5.3 environment. Practical examples for the new and updated tools are provided, together with new information about using Resource Monitoring and to control part of RSCT for performance monitoring. Also, in 10.1, “The performance status (Perfstat) API” on page 584, this book presents the Perfstat API for application programmers to have a better understanding of the new and updated facilities provided with this API.The team that wrote this redbook This redbook was produced by a team of specialists from around the world working at the International Technical Support Organization, Austin Center. Kumiko Hayashi is an IT Specialist working at IBM Japan Systems Engineering Co., Ltd. She has four years of experience in AIX, RS/6000®, and IBM ~ pSeries®. She provides pre-sales technical consultation and post-sales implementation support. She is an IBM Certified Advanced Technical Expert - pSeries and AIX 5L. Kangkook Ji is an IT Specialist at IBM Korea. He has four years of experience in AIX and pSeries. Currently as a Level 2 Support Engineer, he supports field engineers, and his main work is high availability solutions, such as HACMP™ and AIX problems. His interests vary in many IT areas, such as Linux® and middleware. He is an IBM Certified Advanced Technical Expert - pSeries and AIX 5L and HACMP. Octavian Lascu is a Project Leader at the International Technical Support Organization, Poughkeepsie Center. He writes extensively and teaches IBM© Copyright IBM Corp. 2005. All rights reserved. xi
  13. 13. classes worldwide in all areas of pSeries clusters and Linux. Before joining the ITSO, Octavian worked at IBM Global Services Romania as a Software and Hardware Services Manager. He holds a masters degree in Electronic Engineering from the Polytechnical Institute in Bucharest and is also an IBM Certified Advanced Technical Expert in AIX/PSSP/HACMP. He has worked with IBM since 1992. Hennie Pienaar is a Senior Education Specialist in South Africa. He has eight years of experience in the AIX/Linux field. His areas of expertise include AIX, Linux and Tivoli®. He is certified as an Advanced Technical Expert. He has written extensively on AIX and Linux and has delivered classes worldwide on AIX and HACMP. Susan Schreitmueller is a Sr. Consulting I/T Specialist with IBM. She joined IBM eight years ago, specializing in pSeries, AIX, and technical competitive positioning. Susan has been a Systems Administrator on zSeries, iSeries, and pSeries platforms and has expertise in systems administration and resource management. She travels extensively to customer locations, and has a talent for mentoring new hires and working to create a cohesive technical community that shares information at IBM. Tina Tarquinio is a Software Engineer in Poughkeepsie, NY. She has worked at IBM for five years and has three years of AIX System Administration experience working in the pSeries Benchmark Center. She holds a bachelor’s degree in Applied Mathematics and Computer Science from the University of Albany in New York. She is an IBM Certified pSeries AIX System Administrator and an Accredited IT Specialist. James Thompson is a Performance Analyst for IBM Systems Group in Tucson, AZ. He has worked at IBM for five years, the first two years as a Level 2 Support Engineer for Tivoli Storage Manager and for the past three years he has provided performance support for the development of IBM Tape and NAS products. He holds a bachelor’s degree in Computer Science from Utah State University. Thanks to the following people for their contributions to this project: Julie Peet, Certified IBM AIX System Administrator, pSeries Benchmark Center, Poughkeepsie, NY. Nigel Griffiths, Certified IT Specialist, pSeries Advanced Technology Group, United Kingdom Luc Smolders IBM Austinxii AIX 5L Practical Performance Tools and Tuning Guide
  14. 14. Andreas Hoetzel IBM Austin Gabrielle Velez International Technical Support Organization, Rochester Center Scott Vetter IBM Austin Dino Quintero IBM PoughkeepsieBecome a published author Join us for a two- to six-week residency program! Help write an IBM Redbook dealing with specific products or solutions, while getting hands-on experience with leading-edge technologies. Youll team with IBM technical professionals, Business Partners and/or customers. Your efforts will help increase product acceptance and customer satisfaction. As a bonus, youll develop a network of contacts in IBM development labs, and increase your productivity and marketability. Find out more about the residency program, browse the residency index, and apply online at: ibm.com/redbooks/residencies.html Preface xiii
  15. 15. Comments welcome Your comments are important to us! We want our Redbooks™ to be as helpful as possible. Send us your comments about this or other Redbooks in one of the following ways: Use the online Contact us review redbook form found at: ibm.com/redbooks Send your comments in an email to: redbook@us.ibm.com Mail your comments to: IBM Corporation, International Technical Support Organization Dept. JN9B Building 003 Internal Zip 2834 11400 Burnet Road Austin, Texas 78758-3493xiv AIX 5L Practical Performance Tools and Tuning Guide
  16. 16. Part 1Part 1 Introduction Part 1 provides an overview of performance in an AIX 5L V5.3 environment and an introduction to performance analysis and tuning methodology. It also provides a description of overall performance metrics and expectations, together with the system components that should be considered for tuning in an IBM Eserver pSeries running AIX 5L.© Copyright IBM Corp. 2005. All rights reserved. 1
  17. 17. 2 AIX 5L Practical Performance Tools and Tuning Guide
  18. 18. 1 Chapter 1. Performance overview The performance of a computer system is based on human expectations and the ability of the computer system to fulfill these expectations. The objective for performance tuning is to make those expectations and their fulfillment match. The path to achieving this objective is a balance between appropriate expectations and optimizing the available system resources. The performance-tuning process demands skill, knowledge, and experience, and cannot be performed by only analyzing statistics, graphs, and figures. If results are to be achieved, the human aspect of perceived performance must not be neglected. Performance tuning also takes into consideration problem determination aspects as well as pure performance issues.© Copyright IBM Corp. 2005. All rights reserved. 3
  19. 19. 1.1 Performance expectations Performance tuning on a newly installed system usually involves setting the basic parameters for the operating system and applications. The sections in this chapter describe the characteristics of different system resources and provide some advice regarding their base tuning parameters if applicable. Limitations originating from the sizing phase either limit the possibility of tuning, or incur greater cost to overcome them. The system may not meet the original performance expectations because of unrealistic expectations, physical problems in the computer environment, or human error in the design or implementation of the system. In the worst case adding or replacing hardware may be necessary. We therefore advise you to be particularly careful when sizing a system to allow enough capacity for unexpected system loads. In other words, do not design the system to be 100 percent busy from the start of the project. More information about system sizing can be found in the redbook Understanding IBM Eserver pSeries Performance and Sizing, SG24-4810. CPU Network Workload no Manager nfso # of procs PSALLOC vmo Memor Async I/O filesystem al y u layout Virt Ma nage ioo System Tuning me schedo nt LVM Tuning Figure 1-1 System tuning4 AIX 5L Practical Performance Tools and Tuning Guide
  20. 20. When a system in a productive environment still meets the performance expectations for which it was initially designed, but the demands and needs of the utilizing organization have outgrown the system’s basic capacity, performance tuning is performed to avoid and/or delay the cost of adding or replacing hardware. Remember that many performance-related issues can be traced back to operations performed by somebody with limited experience and knowledge, who unintentionally restricted some vital logical or physical resource of the system. To evaluate if you have a performance issue, you can use the flow chart in Figure 1-2 as a guide. START YES CPU bound? Disk YES bound? NO Actions Actions NO NO YES Memory bound? YES Network NO Actions bound? Actions Additional tests Figure 1-2 Performance problem determination flow chart1.1.1 System workload An accurate and complete definition of a systems workload is critical to understanding and/or predicting its performance. A difference in workload can cause far more variation in the measured performance of a system than differences in CPU clock speed or random access memory (RAM) size. The Chapter 1. Performance overview 5
  21. 21. workload definition must include not only the type and rate of requests sent to the system, but also the exact software packages and in-house application programs to be executed. It is important to take into account the work that a system is performing in the background. For example, if a system contains file systems that are NFS-mounted and frequently accessed by other systems, handling those accesses is probably a significant fraction of the overall workload, even though the system is not a designated server. A workload that has been standardized to allow comparisons among dissimilar systems is called a benchmark. However, few real workloads duplicate the exact algorithms and environment of a benchmark. Even industry-standard benchmarks that were originally derived from real applications have been simplified and homogenized to make them portable to a wide variety of hardware and software platforms. The only valid use for industry-standard benchmarks is to narrow the field of candidate systems that will be subjected to a serious evaluation. Therefore, you should not solely rely on benchmark results when trying to understand the workload and performance of your system. It is possible to classify workloads into the following categories: Multiuser A workload that consists of a number of users submitting work through individual terminals. Typically, the performance objectives of such a workload are either to maximize system throughput while preserving a specified worst-case response time or to obtain the best possible response time for a constant workload. Server A workload that consists of requests from other systems. For example, a file-server workload is mostly disk read and disk write requests. It is the disk-I/O component of a multiuser workload (plus NFS or other I/O activity), so the same objective of maximum throughput within a given response-time limit applies. Other server workloads consist of items such as math-intensive programs, database transactions, printer jobs. Workstation A workload that consists of a single user submitting work through a keyboard and receiving results on the display of that system. Typically, the highest-priority performance objective of such a workload is minimum response time to the users requests.1.1.2 Performance objectives After defining the workload that your system will have to process, you can choose performance criteria and set performance objectives based on those criteria. The6 AIX 5L Practical Performance Tools and Tuning Guide
  22. 22. overall performance criteria of computer systems are response time and throughput. Response time is the elapsed time between when a request is submitted and when the response from that request is returned. Examples include: The amount of time a database query takes The amount of time it takes to echo characters to the terminal The amount of time it takes to access a Web page Throughput is a measure of the amount of work that can be accomplished over some unit of time. Examples include: Database transactions per minute Kilobytes of a file transferred per second Kilobytes of a file read or written per second Web server hits per minute The relationship between these metrics is complex. Sometimes you can have higher throughput at the cost of response time or better response time at the cost of throughput. In other situations, a single change can improve both. Acceptable performance is based on reasonable throughput combined with reasonable response time. In planning for or tuning any system, make sure that you have clear objectives for both response time and throughput when processing the specified workload. Otherwise, you risk spending analysis time and resource dollars improving an aspect of system performance that is of secondary importance.1.1.3 Program execution model To clearly examine the performance characteristics of a workload, a dynamic rather than a static model of program execution is necessary, as shown in Figure 1-3 on page 8. Program Execution Hierarchy The figure is a triangle on its base. The left side represents hardware entities that are matched to the appropriate operating system entity on the right side. A program must go from the lowest level of being stored on disk, to the highest level being the processor running program instructions. For instance, from bottom to top, the disk hardware entity holds executable programs; real memory holds waiting operating system threads and interrupt handlers; the translation lookaside buffer holds dispatchable threads; cache Chapter 1. Performance overview 7
  23. 23. contains the currently dispatched thread and the processor pipeline and registers contain the current instruction. Hardware CORE Operating system Current Processor Pipeline and Instruction Level 0 Registers Current Dispatched Cache - L1,L2,L3 Thread Transaction Dispatchable Lookaside Thread Buffer (TLB) Waiting Thread/ Real Interrupt Handlers Memory (RAM) Executable Disk - incl. Programs paging spaceFigure 1-3 Program execution hierarchy To run, a program must make its way up both the hardware and operating system hierarchies in parallel. Each element in the hardware hierarchy is more scarce and more expensive than the element below it. Not only does the program have to contend with other programs for each resource, the transition from one level to the next takes time. To understand the dynamics of program execution, you need a basic understanding of each of the levels in the hierarchy. Hardware hierarchy Usually, the time required to move from one hardware level to another consists primarily of the latency of the lower level (the time from the issuing of a request to the receipt of the first data). Fixed disks The slowest operation for a running program on a standalone system is obtaining code or data from a disk, for the following reasons: The disk controller must be directed to access the specified blocks (queuing delay). The disk arm must seek to the correct cylinder (seek latency).8 AIX 5L Practical Performance Tools and Tuning Guide
  24. 24. The read/write heads must wait until the correct block rotates under them (rotational latency). The data must be transmitted to the controller (transmission time) and then conveyed to the application program (interrupt-handling time).Slow disk operations can have many causes besides explicit read or writerequests in the program. System-tuning activities frequently prove to be hunts forunnecessary disk I/O.Real memoryReal memory, often referred to as Random Access Memory, or RAM, is fasterthan disk, but much more expensive per byte. Operating systems try to keep inRAM only the code and data that are currently in use, storing any excess ontodisk, or never bringing them into RAM in the first place.RAM is not necessarily faster than the processor though. Typically, a RAMlatency of dozens of processor cycles occurs between the time the hardwarerecognizes the need for a RAM access and the time the data or instruction isavailable to the processor.If the access is going to a page of virtual memory that is stored over to disk, orhas not been brought in yet, a page fault occurs, and the execution of theprogram is suspended until the page has been read from disk.Translation Lookaside Buffer (TLB)Programmers are insulated from the physical limitations of the system by theimplementation of virtual memory. You design and code programs as though thememory were very large, and the system takes responsibility for translating theprograms virtual addresses for instructions and data into the real addresses thatare needed to get the instructions and data from RAM. Because thisaddress-translation process can be time-consuming, the system keeps the realaddresses of recently accessed virtual-memory pages in a cache called thetranslation lookaside buffer (TLB).As long as the running program continues to access a small set of program anddata pages, the full virtual-to-real page-address translation does not need to beredone for each RAM access. When the program tries to access avirtual-memory page that does not have a TLB entry, called a TLB miss, dozensof processor cycles, called the TLB-miss latency are required to perform theaddress translation.CachesTo minimize the number of times the program has to experience the RAMlatency, systems incorporate caches for instructions and data. If the required Chapter 1. Performance overview 9
  25. 25. instruction or data is already in the cache, a cache hit results and the instruction or data is available to the processor on the next cycle with no delay. Otherwise, a cache miss occurs with RAM latency. In some systems, there are two or three levels of cache, usually called L1, L2, and L3. If a particular storage reference results in an L1 miss, then L2 is checked. If L2 generates a miss, then the reference goes to the next level, either L3, if it is present, or RAM. Cache sizes and structures vary by model, but the principles of using them efficiently are identical. Pipeline and registers A pipelined, superscalar architecture makes possible, under certain circumstances, the simultaneous processing of multiple instructions. Large sets of general-purpose registers and floating-point registers make it possible to keep considerable amounts of the programs data in registers, rather than continually storing and reloading the data. The optimizing compilers are designed to take maximum advantage of these capabilities. The compilers optimization functions should always be used when generating production programs, however small the programs are. The Optimization and Tuning Guide for XL Fortran, XL C and XL C++ describes how programs can be tuned for maximum performance. Software hierarchy To run, a program must also progress through a series of steps in the software hierarchy. Executable programs When you request a program to run, the operating system performs a number of operations to transform the executable program on disk to a running program. First, the directories in the your current PATH environment variable must be scanned to find the correct copy of the program. Then, the system loader (not to be confused with the ld command, which is the binder) must resolve any external references from the program to shared libraries. To represent your request, the operating system creates a process, or a set of resources, such as a private virtual address segment, which is required by any running program. The operating system also automatically creates a single thread within that process. A thread is the current execution state of a single instance of a program. In AIX, access to the processor and other resources is allocated on a thread10 AIX 5L Practical Performance Tools and Tuning Guide
  26. 26. basis, rather than a process basis. Multiple threads can be created within aprocess by the application program. Those threads share the resources ownedby the process within which they are running.Finally, the system branches to the entry point of the program. If the programpage that contains the entry point is not already in memory (as it might be if theprogram had been recently compiled, executed, or copied), the resultingpage-fault interrupt causes the page to be read from its backing storage.Interrupt handlersThe mechanism for notifying the operating system that an external event hastaken place is to interrupt the currently running thread and transfer control to aninterrupt handler. Before the interrupt handler can run, enough of the hardwarestate must be saved to ensure that the system can restore the context of thethread after interrupt handling is complete. Newly invoked interrupt handlersexperience all of the delays of moving up the hardware hierarchy (except pagefaults). Unless the interrupt handler was run very recently (or the interveningprograms were very economical), it is unlikely that any of its code or dataremains in the TLBs or the caches.When the interrupted thread is dispatched again, its execution context (such asregister contents) is logically restored, so that it functions correctly. However, thecontents of the TLBs and caches must be reconstructed on the basis of theprograms subsequent demands. Thus, both the interrupt handler and theinterrupted thread can experience significant cache-miss and TLB-miss delaysas a result of the interrupt.Waiting threadsWhenever an executing program makes a request that cannot be satisfiedimmediately, such as a synchronous I/O operation (either explicit or as the resultof a page fault), that thread is put in a waiting state until the request is complete.Normally, this results in another set of TLB and cache latencies, in addition to thetime required for the request itself.Dispatchable threadsWhen a thread is dispatchable but not running, it is accomplishing nothing useful.Worse, other threads that are running may cause the threads cache lines to bereused and real memory pages to be reclaimed, resulting in even more delayswhen the thread is finally dispatched. Chapter 1. Performance overview 11
  27. 27. Currently dispatched threads The scheduler chooses the thread that has the strongest claim to the use of the processor. When the thread is dispatched, the logical state of the processor is restored to the state that was in effect when the thread was interrupted. Current machine instructions Most of the machine instructions are capable of executing in a single processor cycle if no TLB or cache miss occurs. In contrast, if a program branches rapidly to different areas of the program and accesses data from a large number of different areas causing high TLB and cache-miss rates, the average number of processor cycles per instruction (CPI) executed might be much greater than one. The program is said to exhibit poor locality of reference. It might be using the minimum number of instructions necessary to do its job, but it is consuming an unnecessarily large number of cycles. In part because of this poor correlation between number of instructions and number of cycles, reviewing a program listing to calculate path length no longer yields a time value directly. While a shorter path is usually faster than a longer path, the speed ratio can be very different from the path-length ratio. The compilers rearrange code in sophisticated ways to minimize the number of cycles required for the execution of the program. The programmer seeking maximum performance must be primarily concerned with ensuring that the compiler has all of the information necessary to optimize the code effectively, rather than trying to second-guess the compilers optimization techniques The real measure of optimization effectiveness is the performance of an authentic workload.1.1.4 System tuning After efficiently implementing application programs, further improvements in the overall performance of your system becomes a matter of system tuning. The main components that are subject to system-level tuning are: Communications I/O Depending on the type of workload and the type of communications link, it might be necessary to tune one or more of the following communications device drivers: TCP/IP, or NFS. Fixed disk The Logical Volume Manager (LVM) controls the placement of file systems and paging spaces on the disk, which can significantly affect the amount of seek latency the system experiences. The disk device drivers control the order in which I/O requests are acted upon.12 AIX 5L Practical Performance Tools and Tuning Guide
  28. 28. Real memory The Virtual Memory Manager (VMM) controls the pool of free real-memory frames and determines when and from where to steal frames to replenish the pool. Running thread The scheduler determines which dispatchable entity should next receive control. In AIX, the dispatchable entity is a thread.1.2 Introduction to the performance tuning process Performance tuning is primarily a matter of resource management and correct system parameters setting. Tuning the workload and the system for efficient resource use consists of the following steps: Identifying the workloads on the system Setting objectives: – Determining how the results will be measured – Quantifying and prioritizing the objectives Identifying the critical resources that limit the systems performance Minimizing the workloads critical-resource requirements: – Using the most appropriate resource, if there is a choice – Reducing the critical-resource requirements of individual programs or system functions – Structuring for parallel resource use Modifying the allocation of resources to reflect priorities – Changing the priority or resource limits of individual programs – Changing the settings of system resource-management parameters Repeating above steps until objectives are met (or resources are saturated) Applying additional resources, if necessary There are appropriate tools for each phase of system performance management Some of the tools are available from IBM; others are the products of third parties. The following figure illustrates the phases of performance management in a simple LAN environment. Chapter 1. Performance overview 13
  29. 29. 1.2.1 Performance management phases Figure 1-4 uses five weighted circles to illustrate the steps of performance tuning a system; plan, install, monitor, tune, and expand. Each circle represents the system in various states of performance; idle, unbalanced, balanced, and overloaded. Essentially, you need to expand a system that is overloaded, tune a system until it is balanced, monitor an unbalanced system and install for more resources when an expansion is necessary. Plan Install Monitor Tune Expand (Idle system) (Unbalanced) (Balanced) (Overloaded) Figure 1-4 Performance phases Identification of the workloads It is essential that all of the work performed by the system be identified. Especially in LAN-connected systems, a complex set of cross-mounted file systems can easily develop with only informal agreement among the users of the systems. These file systems must be identified and taken into account as part of any tuning activity. With multiuser workloads, the analyst must quantify both the typical and peak request rates. It is also important to be realistic about the proportion of the time that a user is actually interacting with the terminal. An important element of this identification stage is determining whether the measurement and tuning activity has to be done on the production system or can be accomplished on another system (or off-shift) with a simulated version of the actual workload. The analyst must weigh the greater authenticity of results from a production environment against the flexibility of the nonproductive environment, where the analyst can perform experiments that risk performance degradation or worse. Importance of setting objectives Although you can set objectives in terms of measurable quantities, the actual desired result is often subjective, such as satisfactory response time. Further, the14 AIX 5L Practical Performance Tools and Tuning Guide
  30. 30. analyst must resist the temptation to tune what is measurable rather than what isimportant. If no system-provided measurement corresponds to the desiredimprovement, that measurement must be devised.The most valuable aspect of quantifying the objectives is not selecting numbersto be achieved, but making a public decision about the relative importance of(usually) multiple objectives. Unless these priorities are set in advance, andunderstood by everyone concerned, the analyst cannot make trade-off decisionswithout incessant consultation. The analyst is also apt to be surprised by thereaction of users or management to aspects of performance that have beenignored. If the support and use of the system crosses organizational boundaries,you might need a written service-level agreement between the providers and theusers to ensure that there is a clear common understanding of the performanceobjectives and priorities.Identification of critical resourcesIn general, the performance of a given workload is determined by the availabilityand speed of one or two critical system resources. The analyst must identifythose resources correctly or risk falling into an endless trial-and-error operation.Systems have both real and logical resources. Critical real resources aregenerally easier to identify, because more system performance tools areavailable to assess the utilization of real resources. The real resources that mostoften affect performance are as follows: CPU cycles Memory I/O bus Various adapters Disk arms/heads/spindles Disk space Network accessLogical resources are less readily identified. Logical resources are generallyprogramming abstractions that partition real resources. The partitioning is doneto share and manage the real resource.Some examples of real resources and the logical resources built on them are asfollows:CPU Processor time sliceMemory Page frames Chapter 1. Performance overview 15
  31. 31. Stacks Buffers Queues Tables Locks and semaphores Disk space Logical volumes File systems Files Partitions Network access Sessions Packets Channels It is important to be aware of logical resources as well as real resources. Threads can be blocked by a lack of logical resources just as for a lack of real resources, and expanding the underlying real resource does not necessarily ensure that additional logical resources will be created. For example, consider the NFS block I/O daemon, biod. A biod daemon on the client is required to handle each pending NFS remote I/O request. The number of biod daemons therefore limits the number of NFS I/O operations that can be in progress simultaneously. When a shortage of biod daemons exists, system instrumentation may indicate that the CPU and communications links are used only slightly. You may have the false impression that your system is underused (and slow), when in fact you have a shortage of biod daemons that is constraining the rest of the resources. A biod daemon uses processor cycles and memory, but you cannot fix this problem simply by adding real memory or converting to a faster CPU. The solution is to create more of the logical resource (biod daemons). Logical resources and bottlenecks can be created inadvertently during application development. A method of passing data or controlling a device may, in effect, create a logical resource. When such resources are created by accident, there are generally no tools to monitor their use and no interface to control their allocation. Their existence may not be appreciated until a specific performance problem highlights their importance. Minimizing critical resource requirements Consider minimizing the workloads critical-resource requirements at three levels, as discussed below.16 AIX 5L Practical Performance Tools and Tuning Guide
  32. 32. Using the appropriate resourceThe decision to use one resource over another should be done consciously andwith specific goals in mind. An example of a resource choice during applicationdevelopment would be a trade-off of increased memory consumption for reducedCPU consumption. A common system configuration decision that demonstratesresource choice is whether to place files locally on an individual workstation orremotely on a server.Reducing the requirement for the critical resourceFor locally developed applications, the programs can be reviewed for ways toperform the same function more efficiently or to remove unnecessary function. Ata system-management level, low-priority workloads that are contending for thecritical resource can be moved to other systems, run at other times, or controlledwith the Workload Manager.Structuring for parallel use of resourcesBecause workloads require multiple system resources to run, take advantage ofthe fact that the resources are separate and can be consumed in parallel. Forexample, the operating system read-ahead algorithm detects the fact that aprogram is accessing a file sequentially and schedules additional sequentialreads to be done in parallel with the applications processing of the previousdata. Parallelism applies to system management as well. For example, if anapplication accesses two or more files at the same time, adding an additionaldisk drive might improve the disk-I/O rate if the files that are accessed at thesame time are placed on different drives.Resource allocation prioritiesThe operating system provides a number of ways to prioritize activities. Some,such as disk pacing, are set at the system level. Others, such as process priority,can be set by individual users to reflect the importance they attach to a specifictask.Repeating the tuning stepsA truism of performance analysis is that there is always a next bottleneck.Reducing the use of one resource means that another resource limits throughputor response time. Suppose, for example, we have a system in which theutilization levels are as follows:CPU: 90% Disk: 70% Memory 60%This workload is CPU-bound. If we successfully tune the workload so that theCPU load is reduced from 90 to 45 percent, we might expect a two-foldimprovement in performance. Unfortunately, the workload is now I/O-limited, withutilizations of approximately the following: Chapter 1. Performance overview 17
  33. 33. CPU: 45% Disk: 90% Memory 60% The improved CPU utilization allows the programs to submit disk requests sooner, but then we hit the limit imposed by the disk drives capacity. The performance improvement is perhaps 30 percent instead of the 100 percent we had envisioned. There is always a new critical resource. The important question is whether we have met the performance objectives with the resources at hand. Attention: Improper system tuning with vmtune, schedtune, and other tuning commands can result in unexpected system behavior like degraded system or application performance, or a system hang. Changes should only be applied when a bottleneck has been identified by performance analysis. Applying additional resources If, after all of the preceding approaches have been exhausted, the performance of the system still does not meet its objectives, the critical resource must be enhanced or expanded. If the critical resource is logical and the underlying real resource is adequate, the logical resource can be expanded at no additional cost. If the critical resource is real, the analyst must investigate some additional questions: How much must the critical resource be enhanced or expanded so that it ceases to be a bottleneck? Will the performance of the system then meet its objectives, or will another resource become saturated first? If there will be a succession of critical resources, is it more cost-effective to enhance or expand all of them, or to divide the current workload with another system? A more detailed diagram of performance management and tuning is presented in Figure 1-5 on page 19.18 AIX 5L Practical Performance Tools and Tuning Guide
  34. 34. 1 - Installation or Migration 2 - Document your 10b - System system change needed 3 - Identify 10a - performance 9 - Apply and manage workload problem or new settings re-analysis 4 - Set performance 7a - Repeat until objectives met or 8 - Record system objectives settings resorces saturated 5 - Identify critical 7 - Establish new resources settings 6 - Minimize resource requirementsFigure 1-5 Performance management cycle Chapter 1. Performance overview 19
  35. 35. 20 AIX 5L Practical Performance Tools and Tuning Guide
  36. 36. 2 Chapter 2. Performance analysis and tuning The performance of a computer system is based on human expectations and the ability of the computer system to fulfill these expectations. The objective for performance tuning is to match expectations and fulfillment. The path to achieving this objective is a balance between appropriate expectations and optimizing the available system resources. The discussion consists of: What can be actually tuned from the systems is categorized into CPU, memory, disk, and network, as discussed in: – “CPU performance” on page 22 – “Memory overview” on page 31 – “Disk I/O performance” on page 37 – “Network performance” on page 48© Copyright IBM Corp. 2005. All rights reserved. 21
  37. 37. 2.1 CPU performance To monitoring and tuning of CPU performance, it is important to know about process and scheduling. This section gives an overview of the process, thread, and scheduling which are closely related to the performance of CPU.2.1.1 Processes and threads An understanding of the way processes and threads operate within the AIX environment is required to successfully monitor and tune AIX for peak CPU throughput. The following defines the differences between threads and processes: Processes A process is an activity within the system that is started with a command, a shell script, or another process. Threads A thread is an independent flow of control that operates within the same address space as other independent flows of controls within a process. A kernel thread is a single sequential flow of control. Kernel threads are owned by a process. A process has one or more kernel threads. The advantage of threads is that you can have multiple threads running in parallel on different CPUs on an SMP system. Applications can be designed to have user level threads that are scheduled to work by the application or by the pthreads scheduler in libpthreads. Multiple threads of control allow an application to service requests from multiple users at the same time. With the libpthreads implementation, user threads sit on top of virtual processors (VP) which are themselves on top of kernel threads. A multi threaded user process can use one of two models, as follows: 1:1 Thread Model: The 1:1 model indicates that each user thread will have exactly one kernel thread mapped to it. This is the default model in early AIX 4.3. In this model, each user thread is bound to a VP and linked to exactly one kernel thread. The VP is not necessarily bound to a real CPU (unless binding to a processor was done). A thread which is bound to a VP is said to have system scope because it is directly scheduled with all the other user threads by the kernel scheduler. M:N Thread Model: The M:N model was implemented in AIX 4.3.1 and has been since then the default model. In this model, several user threads can share the same virtual processor or the same pool of VPs. Each VP can be thought of as a virtual CPU available for executing user code and system calls. A thread which is not bound to a VP is said to be a local or process scope because it is not directly scheduled with all the other threads by the kernel scheduler. The22 AIX 5L Practical Performance Tools and Tuning Guide
  38. 38. pthreads library will handle the scheduling of user threads to the VP and then the kernel will schedule the associated kernel thread. As of AIX 4.3.2, the default is to have one kernel thread mapped to eight user threads. This is tunable from within the application or through an environment variable.The kernel maintains the priority of the threads. A thread’s priority can rangefrom zero to 255. A zero priority is the most favored and 255 is the least favored.Threads can have a fixed or non-fixed priority. The priority of fixed priority threadsdoes not change during the life of the thread, while non-fixed priority threads canhave their maximum priority changed by changing its nice value with the nice orthe renice commands (see 4.3.5, “The nice command” on page 288, and 4.3.6,“The renice command” on page 289).Thread agingWhen a thread is created, the CPU usage value is zero. As the threadaccumulates more time on the CPU, the usage increments. The CPU usage canbe shown with the ps -ef command, looking at the “C” column of the output (seeExample 4-19 on page 212).Every second, the scheduler ages the thread using the following formula: CPU usage = CPU usage*(D/32)Where D is the decay value as set by schedo -o sched_D (see 4.3.4, “Theschedo command” on page 282).If the D parameter is set to 32, the thread usage will not decrease. The default of16 will enable the thread usage to decrease, giving it more time on the CPU.Calculating thread priorityThe kernel calculates the priority for non-fixed priority threads using a formulathat includes the following:base priority The base priority of a thread is 40.nice value The nice value defaults to 20 for foreground processes and 24 for background processes. This can be changed using the nice or renice command.r The CPU penalty factor. The default for r is 16. This value can be changed with the schedo command.D The CPU decay factor. The default for D is 16. This value can be changed with the schedo command.C CPU usage as Thread aging in preceding subsection. Chapter 2. Performance analysis and tuning 23
  39. 39. p_nice This is called the niced priority. It is calculated as from: p_nice = base priority + nice value x_nice The “extra nice” value. If the niced priority for a thread (p_nice) is larger than 60, then the following formula applies: x_nice = p_nice * 2 - 60 If the niced priority for a thread (p_nice) is equal or less than 60, the following formula applies: x_nice = p_nice X The xnice factor is calculated as: (x_nice + 4) / 64. The thread priority is finally calculated based on the following formula: Priority = (C * r/32 * X) + x_nice Using this calculation method, note the following: With the default nice value of 20, the xnice factor is 1, no affect to the priority. When the nice value is bigger than 20, it had greater effect on the x_nice compared to the lower nice value. Smaller values of r reduce the impact of CPU usage to the priority of a thread; therefore the nice value has more of an impact on the system. Scheduling The following scheduling policies apply to AIX: SCHED_RR The thread is time-sliced at a fixed priority. If the thread is still running when the time slice expires, it is moved to the end of the queue of dispatchable threads. The queue the thread will be moved to depends on its priority. Only root can schedule using this policy. SCHED_OTHER This policy only applies to non-fixed priority threads that run with a time slice. The priority gets recalculated at every clock interrupt. This is the default scheduling policy. SCHED_FIFO This is a non-preemptive scheduling scheme except for higher priority threads. Threads run to completion unless they are blocked or relinquish the CPU of their own accord. Only fixed priority threads use this scheduling policy. Only root can change the scheduling policy of threads to use SCHED_FIFO.24 AIX 5L Practical Performance Tools and Tuning Guide
  40. 40. SCHED_FIFO2 Fixed priority threads use this scheduling policy. The thread is put at the head of the run queue if it was only asleep for a short period of time.SCHED_FIFO3 Fixed priority threads use this scheduling policy. The thread is put at the head of the run queue whenever it becomes runnable, but it can be preempted by a higher priority thread.The following section describes important concepts in scheduling.Run queuesEach CPU has a dedicated run queue. A run queue is a list of runnable threads,sorted by thread priority value. There are 256 thread priorities (zero to 255).There is also an additional global run queue where new threads are placed.When the CPU is ready to dispatch a thread, the global run queue is checkedbefore the other run queues are checked. When a thread finishes its time slice onthe CPU, it is placed back on the runqueue of the CPU it was running on. Thishelps AIX to maintain processor affinity. To improve the performance of threadsthat are running with SCHED_OTHER policy and are interrupt driven, you canset the environmental variable called RT_GRQ to ON. This will place the threadon the global run queue. Fixed priority threads will be placed on the global runqueue if you run schedo -o fixed_pri_global=1.Time slicesThe CPUs on the system are shared among all of the threads by giving eachthread a certain slice of time to run. The default time slice of one clock tick (10ms) can be changed using schedo -o timeslice. Sometimes increasing the timeslice improves system throughput due to reduced context switching. The vmstatand sar commands show the amount of context switching. In a high value ofcontext switches, increasing the time slice can improve performance. Thisparameter should, however, only be used after a thorough analysis.Mode switchingThere are two modes that a CPU operates in: kernel mode and user mode. Inuser mode, programs have read and write access to the user data in the processprivate region. They can also read the user text and shared text regions, andhave access to the shared data regions using shared memory functions.Programs also have access to kernel services by using system calls.Programs that operate in kernel mode include interrupt handlers, kernelprocesses, and kernel extensions. Code operating in this mode has read andwrite access to the global kernel address space and to the kernel data in the Chapter 2. Performance analysis and tuning 25
  41. 41. process region when executing within the context of a process. User data within the process address space must be accessed using kernel services. When a user program access system calls, it does so in kernel mode. The concept of user and kernel modes is important to understand when interpreting the output of commands such as vmstat and sar.2.1.2 SMP performance In an SMP system, all of the processors are identical and perform identical functions: Any processor can run any thread on the system. This means that a process or thread ready to run can be dispatched to any processor, except the processes or threads bound to a specific processor using the bindprocessor command. Any processor can handle an external interrupt except interrupt levels bound to a specific processor using the bindintcpu command. Some SMP systems use a first fit interrupt handling in which an interrupt always gets directed to CPU0. If there are multiple interrupts at a time, the second interrupt is directed to CPU1, the third interrupt to CPU2, and so on. A process bound to CPU0 using the bindprocessor command may not get the necessary CPU time to run with best performance in this case. All processors can initiate I/O operations to any I/O device. Cache coherency All processors work with the same virtual and real address space and share the same real memory. However, each processor may have its own cache, holding a small subset of system memory. To guarantee cache coherency the processors use a snooping logic. Each time a word in the cache of a processor is changed, this processor sends a broadcast message over the bus. The processors are “snooping” on the bus, and if they receive a broadcast message about a modified word in the cache of another processor, they need to verify if they hold this changed address in their cache. If they do, they invalidate this entry in their cache. The broadcast messages increase the load on the bus, and invalidated cache entries increase the number of cache misses. Both reduce the theoretical overall system performance, but hardware systems are designed to minimize the impact of the cache coherency mechanism. Processor affinity If a thread is running on a CPU and gets interrupted and redispatched, the thread is placed back on the same CPU (if possible) because the processor’s cache may still have lines that belong to the thread. If it is dispatched to a different CPU, the thread may have to get its information from main memory. Alternatively, it can26 AIX 5L Practical Performance Tools and Tuning Guide

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