Is Parallel Programming Hard, And, If So, What Can You Do About It?

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36 CHAPTER 4. COUNTINGper-thread variables, and should not incur any cachemisses.Quick Quiz 4.25: <strong>What</strong> is with the strange formof the condition on line 3 of Figure 4.11? Why notthe following more intuitive form of the fastpath?3 if (counter + delta
4.3. APPROXIMATE LIMIT COUNTERS 371 static void globalize_count(void)2 {3 globalcount += counter;4 counter = 0;5 globalreserve -= countermax;6 countermax = 0;7 }89 static void balance_count(void)10 {11 countermax = globalcountmax -12 globalcount - globalreserve;13 countermax /= num_online_threads();14 globalreserve += countermax;15 counter = countermax / 2;16 if (counter > globalcount)17 counter = globalcount;18 globalcount -= counter;19 }2021 void count_register_thread(void)22 {23 int idx = smp_thread_id();2425 spin_lock(&gblcnt_mutex);26 counterp[idx] = &counter;27 spin_unlock(&gblcnt_mutex);28 }2930 void count_unregister_thread(int nthreadsexpected)31 {32 int idx = smp_thread_id();3334 spin_lock(&gblcnt_mutex);35 globalize_count();36 counterp[idx] = NULL;37 spin_unlock(&gblcnt_mutex);38 }Figure 4.12: Simple Limit Counter Utility Functionsthe corresponding adjustment to globalreserve.Line 15 sets this thread’s counter to the middleof the range from zero to countermax. Line 16checks to see whether globalcount can in fact accommodatethisvalueofcounter,and, ifnot, line17decreases counter accordingly. Finally, in eithercase, line 18 makes the corresponding adjustmentto globalcount.Lines 21-28 show count_register_thread(),which sets up state for newly created threads. Thisfunction simply installs a pointer to the newly createdthread’s counter variable into the correspondingentry of the counterp[] array under the protectionof gblcnt_mutex.Finally, lines 30-38 show count_unregister_thread(), which tears down state for a soon-tobe-exitingthread. Line 34 acquires gblcnt_mutexand line 37 releases it. Line 35 invokes globalize_count() to clear out this thread’s counter state, andline 36 clears this thread’s entry in the counterp[]array.4.3.3 Simple Limit Counter DiscussionThis type of counter is quite fast when aggregatevalues are near zero, with some overhead due to thecomparison and branch in both add_count()’s andsub_count()’s fastpaths. However, the use of a perthreadcountermaxreservemeansthatadd_count()can fail evenwhen the aggregate value of the counteris nowhere near globalcountmax. Similarly, sub_count() can fail even when the aggregate value ofthe counter is nowhere near zero.In many cases, this is unacceptable. Even if theglobalcountmax is intended to be an approximatelimit, there is usually a limit to exactly how muchapproximation can be tolerated. One way to limitthe degree of approximation is to impose an upperlimit on the value of the per-thread countermax instances.This task is undertaken in the next section.4.3.4 Approximate Limit CounterImplementationBecause this implementation (count_lim_app.c) isquite similar to that in the previous section (Figures4.9, 4.11, and 4.12), only the changes areshown here. Figure 4.13 is identical to Figure 4.9,with the addition of MAX_COUNTERMAX, which setsthe maximum permissible value of the per-threadcountermax variable.Similarly, Figure 4.14 is identical to the balance_count() function in Figure 4.12), with the addition
Page 1 and 2: Is Parallel Programming Hard, And,
Page 3 and 4: Contents1 Introduction 11.1 Histori
Page 5 and 6: CONTENTSv6 Locking 676.1 Staying Al
Page 7 and 8: CONTENTSviiB Synchronization Primit
Page 9 and 10: CONTENTSixE.7.1 Introduction to Pre
Page 11 and 12: PrefaceThe purpose of this book is
Page 13 and 14: Chapter 1IntroductionParallel progr
Page 15 and 16: 1.2. PARALLEL PROGRAMMING GOALS 3CP
Page 17 and 18: 1.3. ALTERNATIVES TO PARALLEL PROGR
Page 19 and 20: 1.4. WHAT MAKES PARALLEL PROGRAMMIN
Page 21 and 22: 1.5. GUIDE TO THIS BOOK 9other hand
Page 23 and 24: Chapter 2Hardware and its HabitsMos
Page 25: 2.1. OVERVIEW 13Therefore, as shown
Page 28 and 29: 16 CHAPTER 2. HARDWARE AND ITS HABI
Page 30 and 31: 18 CHAPTER 2. HARDWARE AND ITS HABI
Page 32 and 33: 20 CHAPTER 3. TOOLS OF THE TRADE1 p
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Page 36 and 37: 24 CHAPTER 3. TOOLS OF THE TRADE1.1
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Page 42 and 43: 30 CHAPTER 4. COUNTING1 atomic_t co
Page 44 and 45: 32 CHAPTER 4. COUNTING4.2.3 Eventua
Page 46 and 47: 34 CHAPTER 4. COUNTINGvanish when t
Page 50 and 51: 38 CHAPTER 4. COUNTING1 unsigned lo
Page 54 and 55: 42 CHAPTER 4. COUNTING1 #define THE
Page 58 and 59: 46 CHAPTER 4. COUNTINGReadsAlgorith
Page 60 and 61: 48 CHAPTER 5. PARTITIONING AND SYNC
Page 80 and 81: 68 CHAPTER 6. LOCKING1 int delete(i
Page 82 and 83: 70 CHAPTER 7. DATA OWNERSHIP
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110 CHAPTER 9. APPLYING RCU1 struct
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112 CHAPTER 9. APPLYING RCU
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114 CHAPTER 10. VALIDATION: DEBUGGI
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116 CHAPTER 11. DATA STRUCTURES
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118 CHAPTER 12. ADVANCED SYNCHRONIZ
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138 CHAPTER 13. EASE OF USEFigure 1
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140 CHAPTER 13. EASE OF USE
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142 CHAPTER 14. TIME MANAGEMENT
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144 CHAPTER 15. CONFLICTING VISIONS
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154 APPENDIX A. IMPORTANT QUESTIONS
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156 APPENDIX A. IMPORTANT QUESTIONS
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158 APPENDIX B. SYNCHRONIZATION PRI
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160 APPENDIX B. SYNCHRONIZATION PRI
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162 APPENDIX C. WHY MEMORY BARRIERS
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184 APPENDIX D. READ-COPY UPDATE IM
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244 APPENDIX E. FORMAL VERIFICATION
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272 APPENDIX F. ANSWERS TO QUICK QU
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330 APPENDIX G. GLOSSARY(2) A physi
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332 APPENDIX G. GLOSSARYnear by. Th
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334 APPENDIX G. GLOSSARY
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336 BIBLIOGRAPHY[But97]USA, March 2
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338 BIBLIOGRAPHY[HMB06][Hol03][HP95
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340 BIBLIOGRAPHY[McK06] Paul E. McK
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342 BIBLIOGRAPHYtor. Software - Pra
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344 BIBLIOGRAPHY[UoC08][VGS08]Berke
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346 APPENDIX H. CREDITSH.4 Original
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