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Program Speedup6x5x4x3x2xLOCALWRITE+BarrierLOCALWRITE+SpecCrossDOMORE+BarrierDOMORE+SpecCrossMANUAL(DOANY+Barrier)1x0x2 4 6 8 10 12 14 16 18 20 22 24Number of ThreadsFigure 5.6: Performance improvement of FLUIDANIMATE using different techniques.and DOMORE. We apply both of them and compare these two implementations with themanual one. As shown in Figure 5.6, DOMORE + Barriers yields the best performanceamong these three. DOMORE does not have the overhead in redundant computation or theoverhead in locking. With small number of threads, LOCALWRITE + Barriers performsbetter than the manual parallelization, implying the overhead in redundant computation isless than the overhead in locking. However, since the redundancy problem deteriorateswith increasing number of threads, the manual implementation scales better than the LO-CALWRITE + Barrier one.All these three parallelization implementations use pthread barriers between inner loops,prohibiting potential parallelism across loop invocations. SPECCROSS can be applied tofurther improve the performance. Figure 5.6 demonstrates the performance gain by usingLOCALWRITE + SPECCROSS. LOCALWRITE + SPECCROSS is always better than90
LOCALWRITE + Barriers because of the additional parallelism enabled by SPECCROSS.However, LOCALWRITE + SPECCROSS does not perform as well as DOMORE + Barrier.The benefits from cross-invocation parallelism is negated by the overhead in redundantcomputation. This also explains why with large thread counts, LOCALWRITE + SPEC-CROSS does not perform as well as the manual parallelization.DOMORE is capable of reducing the redundancy execution and improving the scalabilityof performance. However, SPECCROSS transformation does not support partition-basedparallelization technique such as DOMORE. To make SPECCROSS and DOMORE worktogether to achieve better performance scalability, we modify the DOMORE code generation(section 3.4). Instead of having a separate scheduler thread, the scheduler code isduplicated on each worker thread. This optimization works for FLUIDANIMATE becausethe duplication of scheduler code does not cause any side effect. Figure 5.6 shows thecombiniation of SPECCROSS and DOMORE achieves the best performance among all.Another interesting thing to notice is that compared to DOMORE with pthread barriers,DOMORE with SPECCROSS does not yield much better performance gain. For high confidencespeculation, a speculative distance is applied to avoid conflict-prone speculation.According to the profiling results, some of the loop invocations have very small speculativerange. In that case, speculative barriers basically serve as a non-speculative barrier and theeffect of SPECCROSS is limited.5.5 Limitations of Current Parallelizing Compiler InfrastructureIn the previous sections, we’ve demonstrated the applicability and scalability of DOMOREand SPECCROSS systems using ten programs. Besides these ten programs, DOMORE andSPECCROSS evaluated many other programs. Some of those programs can be directly parallelizedby DOALL, DOANY or PS-DSWP [32, 33, 55], so they are not good candidates91
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AUTOMATICALLY EXPLOITINGCROSS-INVOC
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techniques. Among twenty programs f
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in particular. Their professionalis
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ContentsAbstract . . . . . . . . .
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4.5.4 Load Balancing Techniques . .
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2.4 Sequential Loop Example for DOA
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4.5 Overview of SPECCROSS: At compi
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1.1 Limitations of Existing Approac
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advanced forms of parallelism (MPI,
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the graph stands for an iteration i
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1.2 ContributionsFigure 1.5 demonst
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1.3 Dissertation OrganizationChapte
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alias the array regular via inter-p
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1 for (i = 0; i < M; i++){2 node =
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1 cost = 0;2 node = list->head;3 Wh
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example which cannot benefit from e
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These techniques are referred to as
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unnecessary overhead at runtime.Tab
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Chapter 3Non-Speculatively Exploiti
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for a variety of reasons. For insta
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12x11x10xDOMOREPthread Barrier9xLoo
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Algorithm 1: Pseudo-code for schedu
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Algorithm 2: Pseudo-code for worker
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3.3 Compiler ImplementationThe DOMO
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to T i . DOMORE’s MTCG follows th
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Outer_Preheaderbr BB1ABB1A:ind1 = P
Page 54 and 55: Algorithm 3: Pseudo-code for genera
Page 56 and 57: Scheduler Function SchedulerSync Fu
Page 58 and 59: SchedulerWorker1 Worker2Worker3Work
Page 60 and 61: 3.5 Related Work3.5.1 Cross-invocat
Page 62 and 63: ations during the inspecting proces
Page 64 and 65: for (t = 0; t < STEP; t++) {L1: for
Page 66 and 67: sequential_func() {for (t = 0; t <
Page 68 and 69: Workerthread 1Workerthread 2Workert
Page 70 and 71: library provides efficient misspecu
Page 72 and 73: Workerthread 1TimeFigure 4.6: Timin
Page 74 and 75: 4.2 SPECCROSS Runtime System4.2.1 M
Page 76 and 77: takes up to 200MB memory space.To d
Page 78 and 79: checkpoint, the child spawns new wo
Page 80 and 81: Operation DescriptionFunctions for
Page 82 and 83: Main thread:main() {init();create_t
Page 84 and 85: implemented in the Liberty parallel
Page 86 and 87: Algorithm 5: Pseudo-code for SPECCR
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Page 90 and 91: techniques.Synchronization via sche
Page 92 and 93: Source Benchmark Function % of exec
Page 94 and 95: applied to the outermost loop, gene
Page 96 and 97: 5.2 SPECCROSS Performance Evaluatio
Page 98 and 99: and the number of checking requests
Page 100 and 101: 8x7xno misspec.with misspec.Geomean
Page 102 and 103: This thesisPrevious workSpeedup (x)
Page 106 and 107: for DOMORE and SPECCROSS. Others (e
Page 108 and 109: programs and it achieves a geomean
Page 110 and 111: Bibliography[1] R. Allen and K. Ken
Page 112 and 113: [15] R. Cytron. DOACROSS: Beyond ve
Page 114 and 115: [31] T. B. Jablin, Y. Zhang, J. A.
Page 116 and 117: [47] A. Nicolau, G. Li, A. V. Veide
Page 118 and 119: [62] L. Rauchwerger and D. Padua. T
Page 120: national conference on Parallel Arc
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