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• Dedicated co-processorsthat handle displayoutput.• Increasinglyprogrammable andpowerful• Latest GPUs have over 1TFLOP of peakperformance• CUDA• Hardware Architecture• Programming Model• API to Program the GPU ina C-like environment
• Algorithms which have irregular memoryaccess patterns• Difficult to implement and parallelize withhigh performance on current generationarchitectures• Does not “play nice” with the memory hierarchy▪ Cache/Virtual Memory Issues• Eg: <strong>List</strong> Ranking, Tree Computations etc.
Page 4 and 5: • Classic Irregular Algorithm•
Page 6: • Pointer Jumping Technique for t
Page 9 and 10: Thread Execution Control Unit1 2 M-
Page 11 and 12: CPU / HostKernel 1GridBlocks(0,0)GP
Page 13: • Simple Problem (Sequentially Sp
Page 17 and 18: • A basic technique in parallel c
Page 19: • A basic technique in parallel c
Page 22 and 23: • Use pointer jumping repeatedly
Page 24 and 25: 100001000Time (Milliseconds)1001010
Page 26: • The original algorithm has n th
Page 29 and 30: 40961024256Time (Milliseconds)64164
Page 31 and 32: • Designed for SMPs - Sparse Ruli
Page 33 and 34: SuccessorArrayLocal Ranks2 4 8 1 9
Page 51 and 52: • Assume you select n/log n split
Page 53 and 54:
SuccessorArrayLocal Ranks2 4 8 1 9
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• Each phase is coded as separate
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• Notice that choosing splitters
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• Two factors that contribute to
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• Ordered Lists are Lists with su
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• Parallel Processing of Graphs
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Each edge is replaced with a set of
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• Once an Euler Path is construct
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Load TreeConstruct Euler Path EPPer
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120.00160.00100.00140.00Time (Milli
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• Kernel Cycles consists of• Da
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Memory Transactions128-byte segment
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• Calculations
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• Exploiting massive parallelism
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• 2007 - 2008 Course Work at IIIT
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