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cuda-lecture5-scan.ppt

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cuda-lecture5-scan

? David Kirk/NVIDIA and Wen-mei W. Hwu ECE408/CS483/ECE498al, University of Illinois, 2007-2012 ? David Kirk/NVIDIA and Wen-mei W. Hwu ECE408/CS483/ECE498al, University of Illinois, 2007-2012 * Lecture 5Parallel Computation Patterns – Parallel Prefix Sum (Scan) ? David Kirk/NVIDIA and Wen-mei W. Hwu ECE408/CS483/ECE498al, University of Illinois, 2007-2012 * Objective To master parallel Prefix Sum (Scan) algorithms frequently used for parallel work assignment and resource allocation A key primitive to in many parallel algorithms to convert serial computation into parallel computation Based on reduction tree and reverse reduction tree Reading –Mark Harris, Parallel Prefix Sum with CUDA /compute/cuda/1_1/Website/projects/scan/doc/scan.pdf ? David Kirk/NVIDIA and Wen-mei W. Hwu ECE408/CS483/ECE498al, University of Illinois, 2007-2012 * A Slightly Better Parallel Inclusive Scan Algorithm Read input from device memory to shared memory Each thread reads one value from the inputarray in device memory into shared memory array T0. Thread 0 writes 0 into shared memory array. T0 3 1 7 0 4 1 6 3 ? David Kirk/NVIDIA and Wen-mei W. Hwu ECE408/CS483/ECE498al, University of Illinois, 2007-2012 * A Slightly Better Parallel Scan Algorithm (previous slide) Iterate log(n) times: Threads stride to n: Add pairs of elements stride elements apart. Double stride at each iteration. (note must double buffer shared mem arrays) Active threads: stride to n-1 (n-stride threads) Thread j adds elements j and j-stride from T0 and writes result into shared memory buffer T1 (ping-pong) Iteration #1 Stride = 1 T1 3 4 8 7 4 5 7 9 Stride 1 T0 3 1 7 0 4 1 6 3 ? David Kirk/NVIDIA and Wen-mei W. Hwu ECE408/CS483/ECE498al, University of Illinois, 2007-2012 * A Slightly Better Parallel Scan Algorithm T1 3 4 8 7 4 5 7 9 T0 3 4 11 11 12 12 11 14 Stride 1 Stride 2 Read input from device memory to shared memory. Iterate log(n) times: Threads stride to n: Add pairs of elements stri