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

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48 CHAPTER 5. PARTITIONING AND SYNCHRONIZATION DESIGNP151P5P2423P4P3Figure 5.2: Dining Philosophers Problem, TextbookSolutionThisgeneraltechniqueofnumberingresourcesandacquiring them in numerical order is heavily used asa deadlock-prevention technique. However, it is easyto imagine a sequence of events that will result inonly one philosopher eating at a time even thoughall are hungry:1. P2 picks up fork 1, preventing P1 from takinga fork.2. P3 picks up fork 2.3. P4 picks up fork 3.4. P5 picks up fork 4.5. P5 picks up fork 5 and eats.6. P5 puts down forks 4 and 5.7. P4 picks up fork 4 and eats.PleasethinkaboutwaysofpartitioningtheDiningPhilosophers Problem before reading further.
5.1. PARTITIONING EXERCISES 49P1Lock LHeader LLock RHeader RLock LHeader LLock R0 Header RP4P2Lock LLock RHeader L0 1 Header RP3Lock LHeader LLock R0 1 2 Header RFigure 5.3: Dining Philosophers Problem, PartitionedOne approach is shown in Figure 5.3, which includesfour philosophers rather than five to betterillustrate the partion technique. Here the upper andrightmost philosophers share a pair of forks, whilethe lower and leftmost philosophers share anotherpair of forks. If all philosophers are simultaneouslyhungry, at least two will be able to eat concurrently.In addition, as shown in the figure, the forks cannow be bundled so that the pair are picked up andputdownsimultaneously, simplifying theacquisitionand release algorithms.Quick Quiz 5.1: Is there a better solution to theDining Philosophers Problem?This is an example of “horizontal parallelism”[Inm85] or “data parallelism”, so named becausethere is no dependency among the philosophers.In a data-processing system, a given itemof data would pass through only one of a replicatedset of software components.Quick Quiz 5.2: And in just what sense can this“horizontal parallelism” be said to be “horizontal”?5.1.2 Double-Ended QueueA double-ended queue is a data structure containinga list of elements that may be inserted or removedfrom either end [Knu73]. It has been claimed thata lock-based implementation permitting concurrentoperations on both ends of the double-ended queueis difficult [Gro07]. This section shows how a partitioningdesign strategy can result in a reasonablyLock LHeader LLock R0 1 2 3 Header RFigure 5.4: Double-Ended Queue With Left- andRight-Hand Lockssimple implementation, looking at three general approachesin the following sections.5.1.2.1 Right- and Left-Hand LocksOneseeminglystraightforwardapproachwouldbetohave a left-hand lock for left-hand-end enqueue anddequeue operations along with a right-hand lock forright-hand-end operations, as shown in Figure 5.4.However, the problem with this approach is thatthe two locks’ domains must overlap when there arefewer than four elements on the list. This overlapis due to the fact that removing any given elementaffects not only that element, but also its left- andright-hand neighbors. These domains are indicatedby color in the figure, with blue indicating the domainoftheleft-handlock,redindicatingthedomainof the right-hand lock, and purple indicating overlappingdomains. Although it is possible to createan algorithm that works this way, the fact that ithas no fewer than five special cases should raise abig red flag, especially given that concurrent activityat the other end of the list can shift the queuefrom one special case to another at any time. It isfar better to consider other designs.5.1.2.2 Compound Double-Ended QueueOne way of forcing non-overlapping lock domains isshown in Figure 5.5. Two separate double-ended
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Is Parallel Programming Hard, And,
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Contents1 Introduction 11.1 Histori
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CONTENTSv6 Locking 676.1 Staying Al
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CONTENTSviiB Synchronization Primit
Page 9 and 10: CONTENTSixE.7.1 Introduction to Pre
Page 11 and 12: PrefaceThe purpose of this book is
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Page 15 and 16: 1.2. PARALLEL PROGRAMMING GOALS 3CP
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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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Is Parallel Programming Hard, And, If So, What Can You Do About It?

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