From 1704db3e2875dc845433ea33a3e990f97d4fc1eb Mon Sep 17 00:00:00 2001 From: matt elser Date: Thu, 16 Sep 2021 17:34:29 -0400 Subject: [PATCH 01/15] got cpu versions working --- stream_compaction/cpu.cu | 41 ++++++++++++++++++++++++++++++++++++---- 1 file changed, 37 insertions(+), 4 deletions(-) diff --git a/stream_compaction/cpu.cu b/stream_compaction/cpu.cu index 719fa11..a3182c8 100644 --- a/stream_compaction/cpu.cu +++ b/stream_compaction/cpu.cu @@ -20,6 +20,12 @@ namespace StreamCompaction { void scan(int n, int *odata, const int *idata) { timer().startCpuTimer(); // TODO + odata[0] = 0; + + for (int i = 1; i < n; i++) { + odata[i] = idata[i - 1] + odata[i - 1]; + } + timer().endCpuTimer(); } @@ -30,9 +36,15 @@ namespace StreamCompaction { */ int compactWithoutScan(int n, int *odata, const int *idata) { timer().startCpuTimer(); - // TODO + int oi = 0; + for (int i = 0; i < n; i++) { + if (idata[i] != 0) { + odata[oi] = idata[i]; + oi++; + } + } timer().endCpuTimer(); - return -1; + return oi; } /** @@ -42,9 +54,30 @@ namespace StreamCompaction { */ int compactWithScan(int n, int *odata, const int *idata) { timer().startCpuTimer(); - // TODO + + int* shouldInclude = new int[n]; + int* scan = new int[n]; + + for (int i = 0; i < n; i++) { + shouldInclude[i] = (idata[i] != 0) ? 1 : 0; + } + + scan[0] = 0; + for (int i = 1; i < n ; i++) { + scan[i] = shouldInclude[i-1] + scan[i - 1]; + } + + int lastIndex = 0; + for (int i = 0; i < n; i++) { + if (shouldInclude[i] != 0) { + lastIndex = scan[i]; + odata[lastIndex] = idata[i]; + } + } + delete[] shouldInclude; + delete[] scan; timer().endCpuTimer(); - return -1; + return lastIndex+1; } } } From b4565a743220d1b06d62bed60cbd72c67682eb2b Mon Sep 17 00:00:00 2001 From: matt elser Date: Fri, 17 Sep 2021 00:00:13 -0400 Subject: [PATCH 02/15] got naive gpu implementation working for arrays of size 2^n --- stream_compaction/cpu.cu | 1 - stream_compaction/naive.cu | 62 ++++++++++++++++++++++++++++++++++++-- 2 files changed, 60 insertions(+), 3 deletions(-) diff --git a/stream_compaction/cpu.cu b/stream_compaction/cpu.cu index a3182c8..67730e7 100644 --- a/stream_compaction/cpu.cu +++ b/stream_compaction/cpu.cu @@ -19,7 +19,6 @@ namespace StreamCompaction { */ void scan(int n, int *odata, const int *idata) { timer().startCpuTimer(); - // TODO odata[0] = 0; for (int i = 1; i < n; i++) { diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 4308876..6da7ccf 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -2,6 +2,12 @@ #include #include "common.h" #include "naive.h" +#include + +#ifndef BLOCKSIZE +#define BLOCKSIZE 128 +#endif // !BLOCKSIZE + namespace StreamCompaction { namespace Naive { @@ -11,15 +17,67 @@ namespace StreamCompaction { static PerformanceTimer timer; return timer; } - // TODO: __global__ + __global__ void kernNaiveScan(int n, int *odata, const int *idata, int d) { + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + + if (index >= n) { + return; + } + + if (index >= pow(2, d-1)) { + odata[index] = idata[index - (int)pow(2, d - 1)] + idata[index]; + } + else { + odata[index] = idata[index]; + } + __syncthreads(); + + return; + } /** * Performs prefix-sum (aka scan) on idata, storing the result into odata. */ void scan(int n, int *odata, const int *idata) { timer().startGpuTimer(); - // TODO + + //int* odata2; + int* dev_readable; + int* dev_writeable; + int* swp; // for ping-ponging odata and odata2 + + //int p2Pad = ilog2ceil(n); + + cudaMalloc((void**)&dev_readable, n * sizeof(int)); + cudaMalloc((void**)&dev_writeable, n * sizeof(int)); + + cudaMemcpy(dev_readable, idata, n * sizeof(int), cudaMemcpyHostToDevice); + + int numKernels = ilog2ceil(n); + + // --- begin iterative all-prefix-sum + + for (int d = 1; d <= log2(n); d++) { + + // --- call scan --- + + kernNaiveScan <<>> (n, dev_writeable, dev_readable, d); + checkCUDAErrorFn("naiveScan failed", "naive.cu", 63); + cudaDeviceSynchronize(); + + // --- ping pong buffers --- + + swp = dev_writeable; + dev_writeable = dev_readable; + dev_readable = swp; + } + timer().endGpuTimer(); + + odata[0] = 0; + cudaMemcpy(odata+1, dev_readable, n * sizeof(int), cudaMemcpyDeviceToHost); + cudaFree(dev_readable); + cudaFree(dev_writeable); } } } From 7a3c1bd23259bf54eb9784d8b923cc8004cd717a Mon Sep 17 00:00:00 2001 From: matt elser Date: Fri, 17 Sep 2021 19:31:44 -0400 Subject: [PATCH 03/15] got non-power-of-two naive scan working --- src/main.cpp | 6 ++++-- stream_compaction/naive.cu | 21 +++++++++++---------- 2 files changed, 15 insertions(+), 12 deletions(-) diff --git a/src/main.cpp b/src/main.cpp index 896ac2b..ed67d8f 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -54,11 +54,13 @@ int main(int argc, char* argv[]) { //printArray(SIZE, c, true); printCmpResult(SIZE, b, c); - /* For bug-finding only: Array of 1s to help find bugs in stream compaction or scan + /* + //For bug-finding only: Array of 1s to help find bugs in stream compaction or scan onesArray(SIZE, c); printDesc("1s array for finding bugs"); StreamCompaction::Naive::scan(SIZE, c, a); - printArray(SIZE, c, true); */ + printArray(SIZE, c, true); + */ zeroArray(SIZE, c); printDesc("naive scan, non-power-of-two"); diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 6da7ccf..02e1b25 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -2,7 +2,6 @@ #include #include "common.h" #include "naive.h" -#include #ifndef BLOCKSIZE #define BLOCKSIZE 128 @@ -25,8 +24,8 @@ namespace StreamCompaction { return; } - if (index >= pow(2, d-1)) { - odata[index] = idata[index - (int)pow(2, d - 1)] + idata[index]; + if (index >= (1 << d-1)) { + odata[index] = idata[index - (1 << d - 1)] + idata[index]; } else { odata[index] = idata[index]; @@ -46,22 +45,22 @@ namespace StreamCompaction { int* dev_writeable; int* swp; // for ping-ponging odata and odata2 - //int p2Pad = ilog2ceil(n); + int paddedN = 1 << ilog2ceil(n); - cudaMalloc((void**)&dev_readable, n * sizeof(int)); - cudaMalloc((void**)&dev_writeable, n * sizeof(int)); + cudaMalloc((void**)&dev_readable, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_writeable, paddedN * sizeof(int)); - cudaMemcpy(dev_readable, idata, n * sizeof(int), cudaMemcpyHostToDevice); + cudaMemcpy(dev_readable, idata, paddedN * sizeof(int), cudaMemcpyHostToDevice); int numKernels = ilog2ceil(n); // --- begin iterative all-prefix-sum - for (int d = 1; d <= log2(n); d++) { + for (int d = 1; d <= log2(paddedN); d++) { // --- call scan --- - kernNaiveScan <<>> (n, dev_writeable, dev_readable, d); + kernNaiveScan <<>> (paddedN, dev_writeable, dev_readable, d); checkCUDAErrorFn("naiveScan failed", "naive.cu", 63); cudaDeviceSynchronize(); @@ -74,8 +73,10 @@ namespace StreamCompaction { timer().endGpuTimer(); + // this is an exclusive scan, so the first elem should be 0 + // and we shift everything (except the last elem) one index right odata[0] = 0; - cudaMemcpy(odata+1, dev_readable, n * sizeof(int), cudaMemcpyDeviceToHost); + cudaMemcpy(odata+1, dev_readable, (n-1) * sizeof(int), cudaMemcpyDeviceToHost); cudaFree(dev_readable); cudaFree(dev_writeable); } From aea88d0af3c101193f743b75b101caaf00c21e1b Mon Sep 17 00:00:00 2001 From: matt elser Date: Fri, 17 Sep 2021 21:47:46 -0400 Subject: [PATCH 04/15] got work efficient upsweep working --- stream_compaction/efficient.cu | 66 +++++++++++++++++++++++++++++++++- stream_compaction/naive.cu | 7 ++-- 2 files changed, 67 insertions(+), 6 deletions(-) diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index 2db346e..47163d8 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -3,6 +3,10 @@ #include "common.h" #include "efficient.h" +#ifndef BLOCKSIZE +#define BLOCKSIZE 128 +#endif // !BLOCKSIZE + namespace StreamCompaction { namespace Efficient { using StreamCompaction::Common::PerformanceTimer; @@ -12,13 +16,73 @@ namespace StreamCompaction { return timer; } + + __global__ void kernUpSweep(int n, int *odata, int d) { + + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + int k = index * (1 << (d + 1)); + + if (index > n) { + return; + } + + odata[k + ((1<<(d+1))-1)] = odata[k + (1 << d) - 1] + odata[k + (1 << (d+1)) - 1]; + __syncthreads(); + return; + } + + __global__ void kernDownSweep(int n, int *odata, const int *idata, int d) { + + } + /** * Performs prefix-sum (aka scan) on idata, storing the result into odata. */ void scan(int n, int *odata, const int *idata) { timer().startGpuTimer(); - // TODO + + int* dev_readable; + int* dev_writeable; + + int paddedN = 1 << ilog2ceil(n); + + //cudaMalloc((void**)&dev_readable, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_writeable, paddedN * sizeof(int)); + + cudaMemcpy(dev_writeable, idata, paddedN * sizeof(int), cudaMemcpyHostToDevice); + + // --- up sweep --- + for (int d = 0; d < log2(paddedN); d++) { + int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + //numthreads = numThreads > 0 ? numthreads : 1; + printf("blocksize: %i\t numthreads: %i\n", BLOCKSIZE, numThreads); + kernUpSweep <<>> (numThreads, dev_writeable, d); + checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); + cudaDeviceSynchronize(); + cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); + } + + + // --- down sweep --- + // insert 0 at the end of the in-progress output + //cudaMemcpy(dev_writeable + n - 1, { 0 }, sizeof(int), cudaMemcpyHostToDevice); + cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); + for (int d = 0; d < log2(paddedN); d++) { + //int numThreads = (paddedN - 1) / (1 << d + 1); + //kernDownSweep <<>> (numThreads, dev_writeable, dev_readable, d); + //checkCUDAErrorFn("downSweep failed", "efficent.cu", 70); + //cudaDeviceSynchronize(); + } + timer().endGpuTimer(); + + // this is an exclusive scan, so the first elem should be 0 + // and we shift everything (except the last elem) one index right + odata[0] = 0; // TODO try removing this + cudaMemcpy(odata+1, dev_writeable, (n-1) * sizeof(int), cudaMemcpyDeviceToHost); + cudaFree(dev_readable); + cudaFree(dev_writeable); + } /** diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 02e1b25..0a27e51 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -24,8 +24,8 @@ namespace StreamCompaction { return; } - if (index >= (1 << d-1)) { - odata[index] = idata[index - (1 << d - 1)] + idata[index]; + if (index >= (1 << (d - 1))) { + odata[index] = idata[index - (1 << (d - 1))] + idata[index]; } else { odata[index] = idata[index]; @@ -40,7 +40,6 @@ namespace StreamCompaction { void scan(int n, int *odata, const int *idata) { timer().startGpuTimer(); - //int* odata2; int* dev_readable; int* dev_writeable; int* swp; // for ping-ponging odata and odata2 @@ -52,8 +51,6 @@ namespace StreamCompaction { cudaMemcpy(dev_readable, idata, paddedN * sizeof(int), cudaMemcpyHostToDevice); - int numKernels = ilog2ceil(n); - // --- begin iterative all-prefix-sum for (int d = 1; d <= log2(paddedN); d++) { From fa47dc62c7abfa17624be172c1147f0916a1aaf9 Mon Sep 17 00:00:00 2001 From: matt elser Date: Sat, 18 Sep 2021 12:56:11 -0400 Subject: [PATCH 05/15] got work efficient scan working for powers of 2 --- stream_compaction/efficient.cu | 37 +++++++++++++++++++--------------- 1 file changed, 21 insertions(+), 16 deletions(-) diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index 47163d8..ddc9932 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -20,19 +20,27 @@ namespace StreamCompaction { __global__ void kernUpSweep(int n, int *odata, int d) { int index = (blockIdx.x * blockDim.x) + threadIdx.x; - int k = index * (1 << (d + 1)); - if (index > n) { return; } + int k = index * (1 << (d + 1)); + odata[k + ((1<<(d+1))-1)] = odata[k + (1 << d) - 1] + odata[k + (1 << (d+1)) - 1]; __syncthreads(); - return; } - __global__ void kernDownSweep(int n, int *odata, const int *idata, int d) { + __global__ void kernDownSweep(int n, int *odata, int d) { + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index > n) { + return; + } + int k = index * (1 << (d + 1)); + int t = odata[k + (1 << d) - 1]; + odata[k + (1 << d) - 1] = odata[k + (1 << (d + 1)) - 1]; + odata[k + (1 << (d + 1)) - 1] += t; + __syncthreads(); } /** @@ -54,33 +62,30 @@ namespace StreamCompaction { // --- up sweep --- for (int d = 0; d < log2(paddedN); d++) { int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - //numthreads = numThreads > 0 ? numthreads : 1; - printf("blocksize: %i\t numthreads: %i\n", BLOCKSIZE, numThreads); kernUpSweep <<>> (numThreads, dev_writeable, d); checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); cudaDeviceSynchronize(); cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); } - // --- down sweep --- // insert 0 at the end of the in-progress output - //cudaMemcpy(dev_writeable + n - 1, { 0 }, sizeof(int), cudaMemcpyHostToDevice); + int ZERO = 0; + cudaMemcpy(dev_writeable + n - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); - for (int d = 0; d < log2(paddedN); d++) { - //int numThreads = (paddedN - 1) / (1 << d + 1); - //kernDownSweep <<>> (numThreads, dev_writeable, dev_readable, d); - //checkCUDAErrorFn("downSweep failed", "efficent.cu", 70); - //cudaDeviceSynchronize(); + for (int d = log2(paddedN - 1); d >= 0; d--) { + int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + kernDownSweep <<>> (numThreads, dev_writeable, d); + checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); + cudaDeviceSynchronize(); + cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); } timer().endGpuTimer(); // this is an exclusive scan, so the first elem should be 0 // and we shift everything (except the last elem) one index right - odata[0] = 0; // TODO try removing this - cudaMemcpy(odata+1, dev_writeable, (n-1) * sizeof(int), cudaMemcpyDeviceToHost); - cudaFree(dev_readable); + cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); cudaFree(dev_writeable); } From 6f4a3572190a6da0c2361254b4989c9aba940170 Mon Sep 17 00:00:00 2001 From: matt elser Date: Sat, 18 Sep 2021 20:22:10 -0400 Subject: [PATCH 06/15] work-efficient now works for non-power of two arrays --- stream_compaction/efficient.cu | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index ddc9932..17bd478 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -52,12 +52,13 @@ namespace StreamCompaction { int* dev_readable; int* dev_writeable; + // pad to a power of 2 int paddedN = 1 << ilog2ceil(n); - //cudaMalloc((void**)&dev_readable, paddedN * sizeof(int)); cudaMalloc((void**)&dev_writeable, paddedN * sizeof(int)); - cudaMemcpy(dev_writeable, idata, paddedN * sizeof(int), cudaMemcpyHostToDevice); + // write n items to the GPU array, but offset the start so that the total length is `paddedN` + cudaMemcpy(dev_writeable, idata, n * sizeof(int), cudaMemcpyHostToDevice); // --- up sweep --- for (int d = 0; d < log2(paddedN); d++) { @@ -65,20 +66,20 @@ namespace StreamCompaction { kernUpSweep <<>> (numThreads, dev_writeable, d); checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); cudaDeviceSynchronize(); - cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); + //cudaMemcpy(odata, dev_writeable, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } // --- down sweep --- // insert 0 at the end of the in-progress output int ZERO = 0; - cudaMemcpy(dev_writeable + n - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); + cudaMemcpy(dev_writeable + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); for (int d = log2(paddedN - 1); d >= 0; d--) { int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; kernDownSweep <<>> (numThreads, dev_writeable, d); checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); cudaDeviceSynchronize(); - cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); + //cudaMemcpy(odata, dev_writeable, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } timer().endGpuTimer(); @@ -87,7 +88,6 @@ namespace StreamCompaction { // and we shift everything (except the last elem) one index right cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); cudaFree(dev_writeable); - } /** From e0e41176dd7e7fa9b6eeaa561ed371fd8acd82ea Mon Sep 17 00:00:00 2001 From: matt elser Date: Sat, 18 Sep 2021 22:14:22 -0400 Subject: [PATCH 07/15] finished work efficient compaction (for 2^n and non-2^n sized arrays) --- stream_compaction/common.cu | 17 ++++++- stream_compaction/efficient.cu | 87 ++++++++++++++++++++++++++++------ 2 files changed, 87 insertions(+), 17 deletions(-) diff --git a/stream_compaction/common.cu b/stream_compaction/common.cu index 2ed6d63..3d77c78 100644 --- a/stream_compaction/common.cu +++ b/stream_compaction/common.cu @@ -23,7 +23,13 @@ namespace StreamCompaction { * which map to 0 will be removed, and elements which map to 1 will be kept. */ __global__ void kernMapToBoolean(int n, int *bools, const int *idata) { - // TODO + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index > n) { + return; + } + + bools[index] = idata[index] != 0; + (void)0; } /** @@ -32,7 +38,14 @@ namespace StreamCompaction { */ __global__ void kernScatter(int n, int *odata, const int *idata, const int *bools, const int *indices) { - // TODO + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index > n) { + return; + } + + if (bools[index]) { + odata[indices[index]] = idata[index]; + } } } diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index 17bd478..5abf9dc 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -16,7 +16,6 @@ namespace StreamCompaction { return timer; } - __global__ void kernUpSweep(int n, int *odata, int d) { int index = (blockIdx.x * blockDim.x) + threadIdx.x; @@ -50,44 +49,43 @@ namespace StreamCompaction { timer().startGpuTimer(); int* dev_readable; - int* dev_writeable; + int* dev_odata; // pad to a power of 2 int paddedN = 1 << ilog2ceil(n); - cudaMalloc((void**)&dev_writeable, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_odata, paddedN * sizeof(int)); - // write n items to the GPU array, but offset the start so that the total length is `paddedN` - cudaMemcpy(dev_writeable, idata, n * sizeof(int), cudaMemcpyHostToDevice); + // write n items to the GPU array, the total length is `paddedN`, meaning arr[n:paddedN] are 0 + cudaMemcpy(dev_odata, idata, n * sizeof(int), cudaMemcpyHostToDevice); // --- up sweep --- for (int d = 0; d < log2(paddedN); d++) { int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - kernUpSweep <<>> (numThreads, dev_writeable, d); + kernUpSweep <<>> (numThreads, dev_odata, d); checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); cudaDeviceSynchronize(); - //cudaMemcpy(odata, dev_writeable, paddedN * sizeof(int), cudaMemcpyDeviceToHost); + //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } // --- down sweep --- // insert 0 at the end of the in-progress output int ZERO = 0; - cudaMemcpy(dev_writeable + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); - cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); + cudaMemcpy(dev_odata + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); for (int d = log2(paddedN - 1); d >= 0; d--) { int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - kernDownSweep <<>> (numThreads, dev_writeable, d); + kernDownSweep <<>> (numThreads, dev_odata, d); checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); cudaDeviceSynchronize(); - //cudaMemcpy(odata, dev_writeable, paddedN * sizeof(int), cudaMemcpyDeviceToHost); + //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } timer().endGpuTimer(); // this is an exclusive scan, so the first elem should be 0 // and we shift everything (except the last elem) one index right - cudaMemcpy(odata, dev_writeable, n * sizeof(int), cudaMemcpyDeviceToHost); - cudaFree(dev_writeable); + cudaMemcpy(odata, dev_odata, n * sizeof(int), cudaMemcpyDeviceToHost); + cudaFree(dev_odata); } /** @@ -101,9 +99,68 @@ namespace StreamCompaction { */ int compact(int n, int *odata, const int *idata) { timer().startGpuTimer(); - // TODO + + int paddedN = 1<>>(n, dev_hasElem, dev_idata); + + cudaMemcpy(dev_indices, dev_hasElem, n * sizeof(int), cudaMemcpyDeviceToDevice); + + // --- scan --- + // scanning the `hasElem` "boolean" array yields an array of indices + // idata[i] should be assigned to (if hasElem[i] is truthy). + // why copy (most of the) code from scan() instead of calling it? + // to avoid redundant cudaMalloc/cudaMemcpy calls + + // --- up sweep --- + for (int d = 0; d < log2(paddedN); d++) { + int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + kernUpSweep <<>> (numThreads, dev_indices, d); + checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); + cudaDeviceSynchronize(); + //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); + } + + // --- down sweep --- + // insert 0 at the end of the in-progress output + int ZERO = 0; + cudaMemcpy(dev_indices + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); + for (int d = log2(paddedN - 1); d >= 0; d--) { + int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + kernDownSweep <<>> (numThreads, dev_indices, d); + checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); + cudaDeviceSynchronize(); + //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); + } + + // --- scatter --- + // assign idata -> odata based on the indices calculated by the scan + + Common::kernScatter<<>>(n, dev_odata, dev_idata, dev_hasElem, dev_indices); + timer().endGpuTimer(); - return -1; + + // get the max index for return purposes. This will be whatever is at the end + // of our scattered index array + int maxIndex; + cudaMemcpy(&maxIndex, dev_indices + paddedN - 1, sizeof(int), cudaMemcpyDeviceToHost); + + cudaMemcpy(odata, dev_odata, maxIndex * sizeof(int), cudaMemcpyDeviceToHost); + + cudaFree(dev_odata); + + return maxIndex; } } } From 90b98275b34926eb37ebd32c2ef51427d251c8c5 Mon Sep 17 00:00:00 2001 From: matt elser Date: Sat, 18 Sep 2021 22:56:12 -0400 Subject: [PATCH 08/15] got thrust working --- stream_compaction/thrust.cu | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/stream_compaction/thrust.cu b/stream_compaction/thrust.cu index 1def45e..a2e51d1 100644 --- a/stream_compaction/thrust.cu +++ b/stream_compaction/thrust.cu @@ -19,10 +19,15 @@ namespace StreamCompaction { */ void scan(int n, int *odata, const int *idata) { timer().startGpuTimer(); - // TODO use `thrust::exclusive_scan` - // example: for device_vectors dv_in and dv_out: - // thrust::exclusive_scan(dv_in.begin(), dv_in.end(), dv_out.begin()); + thrust::device_vector dev_odata(odata, odata + n); + thrust::device_vector dev_idata(idata, idata + n); + + thrust::exclusive_scan(dev_idata.begin(), dev_idata.end(), dev_odata.begin()); + timer().endGpuTimer(); + + thrust::copy(dev_odata.begin(), dev_odata.end(), odata); + } } } From a2e9b92013ee7ebb98d0bf39ee0f3aed17610b05 Mon Sep 17 00:00:00 2001 From: matt elser Date: Mon, 20 Sep 2021 15:21:00 -0400 Subject: [PATCH 09/15] optimized thread/block count and removed redundant syncs --- src/main.cpp | 3 +- stream_compaction/efficient.cu | 58 +++++++++++++++++++++------------- stream_compaction/naive.cu | 2 +- stream_compaction/thrust.cu | 2 +- 4 files changed, 39 insertions(+), 26 deletions(-) diff --git a/src/main.cpp b/src/main.cpp index ed67d8f..b346052 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -13,7 +13,7 @@ #include #include "testing_helpers.hpp" -const int SIZE = 1 << 8; // feel free to change the size of array +const int SIZE = 1 << 16; // feel free to change the size of array const int NPOT = SIZE - 3; // Non-Power-Of-Two int *a = new int[SIZE]; int *b = new int[SIZE]; @@ -80,7 +80,6 @@ int main(int argc, char* argv[]) { printDesc("work-efficient scan, non-power-of-two"); StreamCompaction::Efficient::scan(NPOT, c, a); printElapsedTime(StreamCompaction::Efficient::timer().getGpuElapsedTimeForPreviousOperation(), "(CUDA Measured)"); - //printArray(NPOT, c, true); printCmpResult(NPOT, b, c); zeroArray(SIZE, c); diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index 5abf9dc..1c604f5 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -3,8 +3,8 @@ #include "common.h" #include "efficient.h" -#ifndef BLOCKSIZE -#define BLOCKSIZE 128 +#ifndef THREADS_PER_BLOCK +#define THREADS_PER_BLOCK 512 #endif // !BLOCKSIZE namespace StreamCompaction { @@ -26,7 +26,7 @@ namespace StreamCompaction { int k = index * (1 << (d + 1)); odata[k + ((1<<(d+1))-1)] = odata[k + (1 << d) - 1] + odata[k + (1 << (d+1)) - 1]; - __syncthreads(); + //__syncthreads(); } __global__ void kernDownSweep(int n, int *odata, int d) { @@ -39,14 +39,13 @@ namespace StreamCompaction { int t = odata[k + (1 << d) - 1]; odata[k + (1 << d) - 1] = odata[k + (1 << (d + 1)) - 1]; odata[k + (1 << (d + 1)) - 1] += t; - __syncthreads(); + //__syncthreads(); } /** * Performs prefix-sum (aka scan) on idata, storing the result into odata. */ void scan(int n, int *odata, const int *idata) { - timer().startGpuTimer(); int* dev_readable; int* dev_odata; @@ -59,12 +58,19 @@ namespace StreamCompaction { // write n items to the GPU array, the total length is `paddedN`, meaning arr[n:paddedN] are 0 cudaMemcpy(dev_odata, idata, n * sizeof(int), cudaMemcpyHostToDevice); + // The threads/blocks will change per kernel call but declare them here + int numBlocks = ceil( (float)n / THREADS_PER_BLOCK); + int numThreads; + + timer().startGpuTimer(); + // --- up sweep --- for (int d = 0; d < log2(paddedN); d++) { - int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - kernUpSweep <<>> (numThreads, dev_odata, d); + numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); + kernUpSweep <<>> (numThreads, dev_odata, d); checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); - cudaDeviceSynchronize(); + //cudaDeviceSynchronize(); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } @@ -74,9 +80,10 @@ namespace StreamCompaction { cudaMemcpy(dev_odata + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); for (int d = log2(paddedN - 1); d >= 0; d--) { int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - kernDownSweep <<>> (numThreads, dev_odata, d); + numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); + kernDownSweep <<>> (numThreads, dev_odata, d); checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); - cudaDeviceSynchronize(); + //cudaDeviceSynchronize(); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } @@ -98,7 +105,6 @@ namespace StreamCompaction { * @returns The number of elements remaining after compaction. */ int compact(int n, int *odata, const int *idata) { - timer().startGpuTimer(); int paddedN = 1<>>(n, dev_hasElem, dev_idata); + // The threads/blocks will change per kernel call but declare them here + int numBlocks = ceil( (float)n / THREADS_PER_BLOCK); + int numThreads; + + timer().startGpuTimer(); + + Common::kernMapToBoolean<<>>(n, dev_hasElem, dev_idata); cudaMemcpy(dev_indices, dev_hasElem, n * sizeof(int), cudaMemcpyDeviceToDevice); @@ -125,10 +137,11 @@ namespace StreamCompaction { // --- up sweep --- for (int d = 0; d < log2(paddedN); d++) { - int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - kernUpSweep <<>> (numThreads, dev_indices, d); - checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); - cudaDeviceSynchronize(); + numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); + kernUpSweep <<>> (numThreads, dev_indices, d); + checkCUDAErrorFn("upsweep failed", "efficent.cu", 130); + //cudaDeviceSynchronize(); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } @@ -137,17 +150,18 @@ namespace StreamCompaction { int ZERO = 0; cudaMemcpy(dev_indices + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); for (int d = log2(paddedN - 1); d >= 0; d--) { - int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; - kernDownSweep <<>> (numThreads, dev_indices, d); - checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); - cudaDeviceSynchronize(); + numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; + numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); + kernDownSweep <<>> (numThreads, dev_indices, d); + checkCUDAErrorFn("downsweep failed", "efficent.cu", 150); + //cudaDeviceSynchronize(); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } // --- scatter --- // assign idata -> odata based on the indices calculated by the scan - - Common::kernScatter<<>>(n, dev_odata, dev_idata, dev_hasElem, dev_indices); + numBlocks = ceil( (float)n / THREADS_PER_BLOCK); + Common::kernScatter<<>>(n, dev_odata, dev_idata, dev_hasElem, dev_indices); timer().endGpuTimer(); diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 0a27e51..26348ef 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -38,7 +38,6 @@ namespace StreamCompaction { * Performs prefix-sum (aka scan) on idata, storing the result into odata. */ void scan(int n, int *odata, const int *idata) { - timer().startGpuTimer(); int* dev_readable; int* dev_writeable; @@ -51,6 +50,7 @@ namespace StreamCompaction { cudaMemcpy(dev_readable, idata, paddedN * sizeof(int), cudaMemcpyHostToDevice); + timer().startGpuTimer(); // --- begin iterative all-prefix-sum for (int d = 1; d <= log2(paddedN); d++) { diff --git a/stream_compaction/thrust.cu b/stream_compaction/thrust.cu index a2e51d1..ec05030 100644 --- a/stream_compaction/thrust.cu +++ b/stream_compaction/thrust.cu @@ -18,10 +18,10 @@ namespace StreamCompaction { * Performs prefix-sum (aka scan) on idata, storing the result into odata. */ void scan(int n, int *odata, const int *idata) { - timer().startGpuTimer(); thrust::device_vector dev_odata(odata, odata + n); thrust::device_vector dev_idata(idata, idata + n); + timer().startGpuTimer(); thrust::exclusive_scan(dev_idata.begin(), dev_idata.end(), dev_odata.begin()); timer().endGpuTimer(); From 92480c89b56c2c59e417f57954eef3ab08ba6f66 Mon Sep 17 00:00:00 2001 From: matt elser Date: Mon, 20 Sep 2021 21:42:15 -0400 Subject: [PATCH 10/15] fixed bug that caused out of bounds write for large (2^18+) arrays --- stream_compaction/efficient.cu | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index 1c604f5..9bcb6d4 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -4,7 +4,7 @@ #include "efficient.h" #ifndef THREADS_PER_BLOCK -#define THREADS_PER_BLOCK 512 +#define THREADS_PER_BLOCK 128 #endif // !BLOCKSIZE namespace StreamCompaction { @@ -19,7 +19,7 @@ namespace StreamCompaction { __global__ void kernUpSweep(int n, int *odata, int d) { int index = (blockIdx.x * blockDim.x) + threadIdx.x; - if (index > n) { + if (index >= n) { return; } @@ -31,7 +31,7 @@ namespace StreamCompaction { __global__ void kernDownSweep(int n, int *odata, int d) { int index = (blockIdx.x * blockDim.x) + threadIdx.x; - if (index > n) { + if (index >= n) { return; } @@ -69,8 +69,8 @@ namespace StreamCompaction { numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); kernUpSweep <<>> (numThreads, dev_odata, d); - checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); //cudaDeviceSynchronize(); + checkCUDAErrorFn("upsweep failed", "efficent.cu", 50); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } @@ -78,12 +78,13 @@ namespace StreamCompaction { // insert 0 at the end of the in-progress output int ZERO = 0; cudaMemcpy(dev_odata + paddedN - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); + checkCUDAErrorFn("writing 0 failed", "efficent.cu", 81); for (int d = log2(paddedN - 1); d >= 0; d--) { int numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); kernDownSweep <<>> (numThreads, dev_odata, d); - checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); //cudaDeviceSynchronize(); + checkCUDAErrorFn("downsweep failed", "efficent.cu", 70); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } @@ -153,7 +154,7 @@ namespace StreamCompaction { numThreads = ((paddedN - 1) / (1 << (d + 1))) + 1; numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); kernDownSweep <<>> (numThreads, dev_indices, d); - checkCUDAErrorFn("downsweep failed", "efficent.cu", 150); + checkCUDAErrorFn("downsweep failed", "efficent.cu", 151); //cudaDeviceSynchronize(); //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); } @@ -162,6 +163,7 @@ namespace StreamCompaction { // assign idata -> odata based on the indices calculated by the scan numBlocks = ceil( (float)n / THREADS_PER_BLOCK); Common::kernScatter<<>>(n, dev_odata, dev_idata, dev_hasElem, dev_indices); + checkCUDAErrorFn("scatter failed", "efficent.cu", 165); timer().endGpuTimer(); From 0dca1e3e03d2466aaa59a9d1132d0f3bb8b35c13 Mon Sep 17 00:00:00 2001 From: matt elser Date: Mon, 20 Sep 2021 22:50:05 -0400 Subject: [PATCH 11/15] fixed bug for large arrays in naive, started readme --- README.md | 19 +++++++++++++++---- stream_compaction/naive.cu | 9 +++++---- 2 files changed, 20 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 0e38ddb..10852c4 100644 --- a/README.md +++ b/README.md @@ -3,11 +3,22 @@ CUDA Stream Compaction **University of Pennsylvania, CIS 565: GPU Programming and Architecture, Project 2** -* (TODO) YOUR NAME HERE - * (TODO) [LinkedIn](), [personal website](), [twitter](), etc. -* Tested on: (TODO) Windows 22, i7-2222 @ 2.22GHz 22GB, GTX 222 222MB (Moore 2222 Lab) +* Matt Elser + * [LinkedIn](https://www.linkedin.com/in/matt-elser-97b8151ba/), [twitter](twitter.com/__mattelser__ ) +* Tested on: Tested on: Ubuntu 20.04, i3-10100F @ 3.6GHz 16GB, GeForce 1660 Super 6GB + +### Main Features + +### Time Comparison + + +### Known limitations +- [FIXED] The Naive implementation fails for array sizes greater than 2^25. + - Naive was calling an inefficient number of threads, leading to higher-than needed `threadIdx.x` + values. When multiplied to get the `index` this overflowed int and yielded a negative index. + Logic around indices (reasonably) assumed positive values and therefore caused an out of bounds write. +- compact scan fails for array sizes greater than 2^27 due to running out of CPU memory on the (16Gb) test machine. -### (TODO: Your README) Include analysis, etc. (Remember, this is public, so don't put anything here that you don't want to share with the world.) diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 26348ef..72d0740 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -4,7 +4,7 @@ #include "naive.h" #ifndef BLOCKSIZE -#define BLOCKSIZE 128 +#define BLOCKSIZE 512 #endif // !BLOCKSIZE @@ -18,7 +18,7 @@ namespace StreamCompaction { } __global__ void kernNaiveScan(int n, int *odata, const int *idata, int d) { - int index = (blockIdx.x * blockDim.x) + threadIdx.x; + long index = (blockIdx.x * blockDim.x) + threadIdx.x; if (index >= n) { return; @@ -49,6 +49,7 @@ namespace StreamCompaction { cudaMalloc((void**)&dev_writeable, paddedN * sizeof(int)); cudaMemcpy(dev_readable, idata, paddedN * sizeof(int), cudaMemcpyHostToDevice); + checkCUDAErrorFn("memcopy failed", "naive.cu", 51); timer().startGpuTimer(); // --- begin iterative all-prefix-sum @@ -57,9 +58,9 @@ namespace StreamCompaction { // --- call scan --- - kernNaiveScan <<>> (paddedN, dev_writeable, dev_readable, d); - checkCUDAErrorFn("naiveScan failed", "naive.cu", 63); + kernNaiveScan <<>> (paddedN, dev_writeable, dev_readable, d); cudaDeviceSynchronize(); + checkCUDAErrorFn("naiveScan failed", "naive.cu", 63); // --- ping pong buffers --- From 18e885a11989baff98eeefb277a30f1f34f9834d Mon Sep 17 00:00:00 2001 From: matt elser Date: Tue, 21 Sep 2021 12:24:57 -0400 Subject: [PATCH 12/15] add timing functions, progress on readme, and minor bug fixes --- README.md | 14 +++--- src/main.cpp | 92 +++++++++++++++++++++++++++++++++- src/testing_helpers.hpp | 17 +++++++ stream_compaction/efficient.cu | 5 +- stream_compaction/naive.cu | 9 ++-- 5 files changed, 126 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 10852c4..f20dd92 100644 --- a/README.md +++ b/README.md @@ -8,18 +8,20 @@ CUDA Stream Compaction * Tested on: Tested on: Ubuntu 20.04, i3-10100F @ 3.6GHz 16GB, GeForce 1660 Super 6GB ### Main Features +This project implements an exclusive scan (performing an operation on (in this case a sum of) all previous +elements along an array) and stream compaction (removing elements from an array based on a condition) using +the CPU, GPU with CUDA, and the CUDA powered library `Thrust`. ### Time Comparison +The test setup in `main.cpp` has been coopted to set up repeated timings to remove noise from measurements. +![timing data table](img/timingData.png) +### Block Size Comparison +changing the number of threads per block ### Known limitations - [FIXED] The Naive implementation fails for array sizes greater than 2^25. - Naive was calling an inefficient number of threads, leading to higher-than needed `threadIdx.x` values. When multiplied to get the `index` this overflowed int and yielded a negative index. Logic around indices (reasonably) assumed positive values and therefore caused an out of bounds write. -- compact scan fails for array sizes greater than 2^27 due to running out of CPU memory on the (16Gb) test machine. - - -Include analysis, etc. (Remember, this is public, so don't put -anything here that you don't want to share with the world.) - +- compact scan fails for array sizes greater than 2^28 due to running out of CPU memory on the (16Gb) test machine. diff --git a/src/main.cpp b/src/main.cpp index b346052..49a80a7 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -11,9 +11,10 @@ #include #include #include +#include #include "testing_helpers.hpp" -const int SIZE = 1 << 16; // feel free to change the size of array +const int SIZE = 1 << 22; // feel free to change the size of array const int NPOT = SIZE - 3; // Non-Power-Of-Two int *a = new int[SIZE]; int *b = new int[SIZE]; @@ -148,6 +149,95 @@ int main(int argc, char* argv[]) { //printArray(count, c, true); printCmpLenResult(count, expectedNPOT, b, c); + // --- repeated timing --- + int NUM_TIMINGS = 100; + std::vector data; + float stdDev; + float mean; + + printf("\n BlockSize = 128\n"); + printf(" Data gathered from %i runs with array size %i (2^%i)\n", NUM_TIMINGS, SIZE, ilog2(SIZE)); + printf("--------------------------------------------------------------\n\n"); + printf("------------------------------| mean (ms) |--| stdDev (ms) |--\n"); + printf("------ Scan ------\n"); + + // CPU + /* + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::CPU::scan(SIZE, c, a); + data.push_back(StreamCompaction::CPU::timer().getCpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("CPU Scan \t%f\t%f\n", mean, stdDev); + data.clear(); + */ + + // Naive + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::Naive::scan(SIZE, c, a); + data.push_back(StreamCompaction::Naive::timer().getGpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("Naive GPU Scan \t%f\t%f\n", mean, stdDev); + data.clear(); + + // work efficient + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::Efficient::scan(SIZE, c, a); + data.push_back(StreamCompaction::Efficient::timer().getGpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("Work Efficient GPU Scan \t%f\t%f\n", mean, stdDev); + data.clear(); + + // work efficient + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::Thrust::scan(SIZE, c, a); + data.push_back(StreamCompaction::Thrust::timer().getGpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("Thrust Library Scan \t%f\t%f\n", mean, stdDev); + data.clear(); + + printf("----- Compact -----\n"); + + // CPU + /* + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::CPU::compactWithoutScan(SIZE, b, a); + data.push_back(StreamCompaction::CPU::timer().getCpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("CPU compact without Scan \t%f\t%f\n", mean, stdDev); + data.clear(); + + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::CPU::compactWithScan(SIZE, b, a); + data.push_back(StreamCompaction::CPU::timer().getCpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("CPU compact with Scan \t%f\t%f\n", mean, stdDev); + data.clear(); + */ + + // work efficient + for (int i = 0; i < NUM_TIMINGS; i++) { + zeroArray(SIZE, c); + StreamCompaction::Efficient::compact(SIZE, c, a); + data.push_back(StreamCompaction::Efficient::timer().getGpuElapsedTimeForPreviousOperation()); + } + tabulate(&data, &mean, &stdDev); + printf("Work Efficient GPU compact\t%f\t%f\n", mean, stdDev); + data.clear(); + + std::cout << std::endl; + system("pause"); // stop Win32 console from closing on exit delete[] a; delete[] b; diff --git a/src/testing_helpers.hpp b/src/testing_helpers.hpp index 025e94a..feef968 100644 --- a/src/testing_helpers.hpp +++ b/src/testing_helpers.hpp @@ -5,6 +5,7 @@ #include #include #include +#include template int cmpArrays(int n, T *a, T *b) { @@ -74,3 +75,19 @@ void printElapsedTime(T time, std::string note = "") { std::cout << " elapsed time: " << time << "ms " << note << std::endl; } + +void tabulate(std::vector* data, float* mean, float* stdDev) { + float sum = 0; + for (auto i : *data) { + sum += i; + } + *mean = sum / data->size(); + + float variance = 0; + for (auto i : *data) { + variance += (i - *mean) * (i - *mean); + } + variance /= data->size(); + + *stdDev = sqrt(variance); +} diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index 9bcb6d4..e098b2b 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -4,7 +4,7 @@ #include "efficient.h" #ifndef THREADS_PER_BLOCK -#define THREADS_PER_BLOCK 128 +#define THREADS_PER_BLOCK 256 #endif // !BLOCKSIZE namespace StreamCompaction { @@ -175,6 +175,9 @@ namespace StreamCompaction { cudaMemcpy(odata, dev_odata, maxIndex * sizeof(int), cudaMemcpyDeviceToHost); cudaFree(dev_odata); + cudaFree(dev_idata); + cudaFree(dev_hasElem); + cudaFree(dev_indices); return maxIndex; } diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 72d0740..5dfda31 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -4,9 +4,12 @@ #include "naive.h" #ifndef BLOCKSIZE -#define BLOCKSIZE 512 +#define BLOCKSIZE 256 #endif // !BLOCKSIZE +#include + + namespace StreamCompaction { namespace Naive { @@ -57,8 +60,8 @@ namespace StreamCompaction { for (int d = 1; d <= log2(paddedN); d++) { // --- call scan --- - - kernNaiveScan <<>> (paddedN, dev_writeable, dev_readable, d); + float numBlocks = ceil((float)n / BLOCKSIZE); + kernNaiveScan <<>> (paddedN, dev_writeable, dev_readable, d); cudaDeviceSynchronize(); checkCUDAErrorFn("naiveScan failed", "naive.cu", 63); From 79272195feddee5b5f7b340875be7561a2f2f96d Mon Sep 17 00:00:00 2001 From: matt elser Date: Tue, 21 Sep 2021 13:20:04 -0400 Subject: [PATCH 13/15] filled out readme and added images --- README.md | 22 +++++++++++++++++++--- img/blockComparison.png | Bin 0 -> 42597 bytes img/timingData.png | Bin 0 -> 13174 bytes src/main.cpp | 7 +------ 4 files changed, 20 insertions(+), 9 deletions(-) create mode 100644 img/blockComparison.png create mode 100644 img/timingData.png diff --git a/README.md b/README.md index f20dd92..1c509dd 100644 --- a/README.md +++ b/README.md @@ -15,13 +15,29 @@ the CPU, GPU with CUDA, and the CUDA powered library `Thrust`. ### Time Comparison The test setup in `main.cpp` has been coopted to set up repeated timings to remove noise from measurements. ![timing data table](img/timingData.png) +CPU scan and compact may be faster for smaller arrays, but the efficient GPU algorithms become more efficient +at array size 2^16^ for compact and 2^17^ for efficient scan. ### Block Size Comparison -changing the number of threads per block +changing the number of threads per blocks did not have a noticeable impact on timing. Minor differences are +can be seen in the tables below, but almost all are around one standard deviation of another, so this may just +be noise. +![block comparison tables](img/blockComparison.png) ### Known limitations -- [FIXED] The Naive implementation fails for array sizes greater than 2^25. +- [FIXED] The Naive implementation fails for array sizes greater than 2^25^. - Naive was calling an inefficient number of threads, leading to higher-than needed `threadIdx.x` values. When multiplied to get the `index` this overflowed int and yielded a negative index. Logic around indices (reasonably) assumed positive values and therefore caused an out of bounds write. -- compact scan fails for array sizes greater than 2^28 due to running out of CPU memory on the (16Gb) test machine. +- compact scan fails for array sizes greater than 2^28^ due to running out of CPU memory on the (16Gb) test machine. + +### Extra Credit +- Work Efficient GPU algorithms are more efficient than CPU (for large array sizes). This was achieved + by removing divergent threads from `upsweep` and `downsweep` kernel calls. Prior to the discussion in class of + modifying the indexing for optimal thread scheduling, these algorithms were implemented to acheive the same end + iteratively. Each layer is a separate kernel call, and each kernel call only spawns one thread per index being + written to (i.e. n/2 for the first call, n/4 for the next, etc.). This does not have the same benefit of contiguous + memory reads, however. Of note, this iterative method does simplify syncing of threads/kernels. No threads on any + given layer are reading/writing from/to any of the indices being read/written from/to by any other thread. Since + All layers are separate kernel calls (on the default stream and therefore with an implicit join/sync), so no + explicit syncs are needed. diff --git a/img/blockComparison.png b/img/blockComparison.png new file mode 100644 index 0000000000000000000000000000000000000000..21cdd0e050b452c34545bc36b0028c1dc362a888 GIT binary patch literal 42597 zcmeFZc|6o_-~T-Z*}hqevQ8nDqzzezHYBN3wir>#mZEHfp%fA$Ey^}ZNR}bXB*v($ zAz6nRj9nUI3}!Ri{qa4&=XIXfZ@I4Pz8?4EasTf7asFYB$N0=Ka~#L#_#DUkeY~FU zchb4D)|(}jB|#w2W?P#R7eF8|1OyWPEWQc&PoeN)3Q!1zT(CX{D*vIn0K5_Lv9h-U zfhv(w+^eF%dx_gNE+HV0^tX*ap|+s+*Fd0xb=wnG7sEX$Im8I^=kikyLZ)L~9;3F( zceEG0>CZLO!J<|Z_Q5mBt>0LTTATY@K=*M587~AJl7P>Y0>1S2E^%3)II1Qh4iwqa zU=g4=D<%X6ilPS~ArL6G-zpY()3gAw1d55fvJjxSZSsG5wdJQ=4xi1V;so-{EaJR4 zhJ(OCNrKT@kH$tmFGg^N%wh9+O!_QC2*kQ53t0}GdEh2;D(`lp^^O%0p{cT71|m$z zi`u)|hR0D!sGq6rV306aWL(;qwS>8wH~ZkHoN|vWXuaLlAeR6hH%7q8v>?S$9R-BRD;%A- z6oUMahx74UP%NZVJDi2(>Q!TnblWH`s~yot zf09n4nVm}tB$3t|=X<{ryjrHfqmjLxhsUw550n9n`ku8{dc0M6OD1L;IQ%lzDh 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ze#f~t^CnnL6rH_D;(|1=J#JroO3GQxt3}YfqALZSVNhMd%i0B_Z&jc9@)t_Mp6U|J z$epCWA{46GH6ZZn?~ZatH_T(l)w<*(cxv_Y-2BamkLm?+YM)K=PTjuLze43R+8+1W zDMqO@e%unP7JW?FCHg4vzoxqXd!OG>5-I-;t)BnK51HUV1psqYmsJdJmKP~)QaOF< L9K6)w`jh_$4rl-- literal 0 HcmV?d00001 diff --git a/src/main.cpp b/src/main.cpp index 49a80a7..8f4a36f 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -14,7 +14,7 @@ #include #include "testing_helpers.hpp" -const int SIZE = 1 << 22; // feel free to change the size of array +const int SIZE = 1 << 16; // feel free to change the size of array const int NPOT = SIZE - 3; // Non-Power-Of-Two int *a = new int[SIZE]; int *b = new int[SIZE]; @@ -155,14 +155,12 @@ int main(int argc, char* argv[]) { float stdDev; float mean; - printf("\n BlockSize = 128\n"); printf(" Data gathered from %i runs with array size %i (2^%i)\n", NUM_TIMINGS, SIZE, ilog2(SIZE)); printf("--------------------------------------------------------------\n\n"); printf("------------------------------| mean (ms) |--| stdDev (ms) |--\n"); printf("------ Scan ------\n"); // CPU - /* for (int i = 0; i < NUM_TIMINGS; i++) { zeroArray(SIZE, c); StreamCompaction::CPU::scan(SIZE, c, a); @@ -171,7 +169,6 @@ int main(int argc, char* argv[]) { tabulate(&data, &mean, &stdDev); printf("CPU Scan \t%f\t%f\n", mean, stdDev); data.clear(); - */ // Naive for (int i = 0; i < NUM_TIMINGS; i++) { @@ -206,7 +203,6 @@ int main(int argc, char* argv[]) { printf("----- Compact -----\n"); // CPU - /* for (int i = 0; i < NUM_TIMINGS; i++) { zeroArray(SIZE, c); StreamCompaction::CPU::compactWithoutScan(SIZE, b, a); @@ -224,7 +220,6 @@ int main(int argc, char* argv[]) { tabulate(&data, &mean, &stdDev); printf("CPU compact with Scan \t%f\t%f\n", mean, stdDev); data.clear(); - */ // work efficient for (int i = 0; i < NUM_TIMINGS; i++) { From 8b76b3926ca2a78841364bd770ede22bb3a12526 Mon Sep 17 00:00:00 2001 From: matt elser Date: Tue, 21 Sep 2021 22:36:46 -0400 Subject: [PATCH 14/15] add radix sort extra credit --- README.md | 10 +- src/main.cpp | 48 +++++++- stream_compaction/CMakeLists.txt | 2 + stream_compaction/common.cu | 5 +- stream_compaction/efficient.cu | 2 +- stream_compaction/naive.cu | 2 +- stream_compaction/radix.cu | 197 +++++++++++++++++++++++++++++++ stream_compaction/radix.h | 11 ++ stream_compaction/thrust.cu | 12 ++ stream_compaction/thrust.h | 1 + 10 files changed, 281 insertions(+), 9 deletions(-) create mode 100644 stream_compaction/radix.cu create mode 100644 stream_compaction/radix.h diff --git a/README.md b/README.md index 1c509dd..cfb4cf0 100644 --- a/README.md +++ b/README.md @@ -4,13 +4,16 @@ CUDA Stream Compaction **University of Pennsylvania, CIS 565: GPU Programming and Architecture, Project 2** * Matt Elser - * [LinkedIn](https://www.linkedin.com/in/matt-elser-97b8151ba/), [twitter](twitter.com/__mattelser__ ) + * [LinkedIn](https://www.linkedin.com/in/matt-elser-97b8151ba/), [twitter](twitter.com/__mattelser__) * Tested on: Tested on: Ubuntu 20.04, i3-10100F @ 3.6GHz 16GB, GeForce 1660 Super 6GB ### Main Features This project implements an exclusive scan (performing an operation on (in this case a sum of) all previous elements along an array) and stream compaction (removing elements from an array based on a condition) using the CPU, GPU with CUDA, and the CUDA powered library `Thrust`. +- all required algorithms work +- Efficient scan and compaction are faster than CPU implementation for arrays of sufficient size +- Radix sort has been implemented (without tiling or bitonic merge) ### Time Comparison The test setup in `main.cpp` has been coopted to set up repeated timings to remove noise from measurements. @@ -41,3 +44,8 @@ be noise. given layer are reading/writing from/to any of the indices being read/written from/to by any other thread. Since All layers are separate kernel calls (on the default stream and therefore with an implicit join/sync), so no explicit syncs are needed. +- Radix sort has been implemented, though without tiling or bitonic merge. It sorts correctly for all array sizes (power of two + and non-power of two) up until 2^27, at which point the test machine runs out of memory. Radix sorting has been + validated against `Thrust`'s sort (though the timing of the two are different by several orders of magnitude). + The algorithm has not been optimized to use shared memory or contiguous memory reads, and would fail for arrays with + negative values. diff --git a/src/main.cpp b/src/main.cpp index 8f4a36f..6a65ca2 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -10,11 +10,12 @@ #include #include #include +#include #include #include #include "testing_helpers.hpp" -const int SIZE = 1 << 16; // feel free to change the size of array +const int SIZE = 1 << 26; // feel free to change the size of array const int NPOT = SIZE - 3; // Non-Power-Of-Two int *a = new int[SIZE]; int *b = new int[SIZE]; @@ -150,6 +151,11 @@ int main(int argc, char* argv[]) { printCmpLenResult(count, expectedNPOT, b, c); // --- repeated timing --- + printf("\n"); + printf("******************************\n"); + printf("** SCAN & COMPACTION TIMING **\n"); + printf("******************************\n"); + int NUM_TIMINGS = 100; std::vector data; float stdDev; @@ -230,11 +236,47 @@ int main(int argc, char* argv[]) { tabulate(&data, &mean, &stdDev); printf("Work Efficient GPU compact\t%f\t%f\n", mean, stdDev); data.clear(); - - std::cout << std::endl; + + // --- Radix Sort --- + + printf("\n"); + printf("******************************\n"); + printf("********* RADIX SORT *********\n"); + printf("******************************\n"); + + genArray(SIZE, a, 50); + printArray(SIZE, a, true); + + zeroArray(SIZE, b); + printDesc("thrust sort, power-of-two"); + StreamCompaction::Thrust::sort(SIZE, b, a); + printElapsedTime(StreamCompaction::Thrust::timer().getGpuElapsedTimeForPreviousOperation(), "(CUDA Measured)"); + printArray(SIZE, b, true); + + zeroArray(SIZE, c); + printDesc("radix sort, power-of-two"); + StreamCompaction::Radix::sort(SIZE, c, a); + printElapsedTime(StreamCompaction::Radix::timer().getGpuElapsedTimeForPreviousOperation(), "(CUDA Measured)"); + printArray(SIZE, c, true); + printCmpResult(SIZE, b, c); + + zeroArray(NPOT, b); + printDesc("thrust sort, non-power-of-two"); + StreamCompaction::Thrust::sort(NPOT, b, a); + printElapsedTime(StreamCompaction::Thrust::timer().getGpuElapsedTimeForPreviousOperation(), "(CUDA Measured)"); + printArray(NPOT, b, true); + + zeroArray(NPOT, c); + printDesc("radix sort, non-power-of-two"); + StreamCompaction::Radix::sort(NPOT, c, a); + printElapsedTime(StreamCompaction::Radix::timer().getGpuElapsedTimeForPreviousOperation(), "(CUDA Measured)"); + + printArray(NPOT, c, true); + printCmpResult(NPOT, b, c); system("pause"); // stop Win32 console from closing on exit delete[] a; delete[] b; delete[] c; } + diff --git a/stream_compaction/CMakeLists.txt b/stream_compaction/CMakeLists.txt index 567795b..eb71175 100644 --- a/stream_compaction/CMakeLists.txt +++ b/stream_compaction/CMakeLists.txt @@ -4,6 +4,7 @@ set(headers "naive.h" "efficient.h" "thrust.h" + "radix.h" ) set(sources @@ -12,6 +13,7 @@ set(sources "naive.cu" "efficient.cu" "thrust.cu" + "radix.cu" ) list(SORT headers) diff --git a/stream_compaction/common.cu b/stream_compaction/common.cu index 3d77c78..5d3eb74 100644 --- a/stream_compaction/common.cu +++ b/stream_compaction/common.cu @@ -24,12 +24,11 @@ namespace StreamCompaction { */ __global__ void kernMapToBoolean(int n, int *bools, const int *idata) { int index = (blockIdx.x * blockDim.x) + threadIdx.x; - if (index > n) { + if (index >= n) { return; } bools[index] = idata[index] != 0; - (void)0; } /** @@ -39,7 +38,7 @@ namespace StreamCompaction { __global__ void kernScatter(int n, int *odata, const int *idata, const int *bools, const int *indices) { int index = (blockIdx.x * blockDim.x) + threadIdx.x; - if (index > n) { + if (index >= n) { return; } diff --git a/stream_compaction/efficient.cu b/stream_compaction/efficient.cu index e098b2b..1759d44 100644 --- a/stream_compaction/efficient.cu +++ b/stream_compaction/efficient.cu @@ -4,7 +4,7 @@ #include "efficient.h" #ifndef THREADS_PER_BLOCK -#define THREADS_PER_BLOCK 256 +#define THREADS_PER_BLOCK 512 #endif // !BLOCKSIZE namespace StreamCompaction { diff --git a/stream_compaction/naive.cu b/stream_compaction/naive.cu index 5dfda31..1229fa6 100644 --- a/stream_compaction/naive.cu +++ b/stream_compaction/naive.cu @@ -4,7 +4,7 @@ #include "naive.h" #ifndef BLOCKSIZE -#define BLOCKSIZE 256 +#define BLOCKSIZE 512 #endif // !BLOCKSIZE #include diff --git a/stream_compaction/radix.cu b/stream_compaction/radix.cu new file mode 100644 index 0000000..3488b5a --- /dev/null +++ b/stream_compaction/radix.cu @@ -0,0 +1,197 @@ +#include +#include +#include "common.h" +#include "radix.h" + +#ifndef THREADS_PER_BLOCK +#define THREADS_PER_BLOCK 128 +#endif // !BLOCKSIZE + +namespace StreamCompaction { + namespace Radix { + using StreamCompaction::Common::PerformanceTimer; + PerformanceTimer& timer() + { + static PerformanceTimer timer; + return timer; + } + + __global__ void kernUpSweep(int n, int* odata, int d) { + + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index >= n) { + return; + } + + int k = index * (1 << (d + 1)); + + odata[k + ((1 << (d + 1)) - 1)] = odata[k + (1 << d) - 1] + odata[k + (1 << (d + 1)) - 1]; + } + + __global__ void kernDownSweep(int n, int* odata, int d) { + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index >= n) { + return; + } + + int k = index * (1 << (d + 1)); + int t = odata[k + (1 << d) - 1]; + odata[k + (1 << d) - 1] = odata[k + (1 << (d + 1)) - 1]; + odata[k + (1 << (d + 1)) - 1] += t; + } + + __global__ void kernInvertBoolean(int n, int* bools, const int* idata) { + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index >= n) { + return; + } + + bools[index] = !idata[index]; + } + + __global__ void kernMapBitToBooleans(int n, int bit, int *boolsZero, int *boolsOne, const int *idata) { + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index >= n) { + return; + } + + // adapted from stack overflow answer by Sparky: + // https://stackoverflow.com/questions/8011700/how-do-i-extract-specific-n-bits-of-a-32-bit-unsigned-integer-in-c + int mask = 1 << bit; + int isolatedBit = (idata[index] & mask) >> bit; + + boolsOne[index] = isolatedBit; + boolsZero[index] = !isolatedBit; + } + + __global__ void kernAddConstant(int n, const int incr, int* odata) { + // this was simpler than adding a conditional to up/down sweep, + // had they been implemented differently this could make more sense there + int index = (blockIdx.x * blockDim.x) + threadIdx.x; + if (index >= n) { + return; + } + + odata[index] += incr; + } + + void scanWithOffset(int n, int* dev_odata, int offset = 0) { + int numThreads; + int numBlocks; + + // --- up sweep --- + for (int d = 0; d < log2(n); d++) { + numThreads = ((n - 1) / (1 << (d + 1))) + 1; + numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); + kernUpSweep << > > (numThreads, dev_odata, d); + checkCUDAErrorFn("upsweep failed", "radix.cu", 50); + //cudaDeviceSynchronize(); + //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); + } + + // --- down sweep --- + // insert 0 at the end of the in-progress output + int ZERO = 0; + cudaMemcpy(dev_odata + n - 1, &ZERO, sizeof(int), cudaMemcpyHostToDevice); + for (int d = log2(n - 1); d >= 0; d--) { + numThreads = ((n - 1) / (1 << (d + 1))) + 1; + numBlocks = ceil((float)numThreads / THREADS_PER_BLOCK); + kernDownSweep << > > (numThreads, dev_odata, d); + checkCUDAErrorFn("downsweep failed", "radix.cu", 65); + //cudaDeviceSynchronize(); + //cudaMemcpy(odata, dev_odata, paddedN * sizeof(int), cudaMemcpyDeviceToHost); + } + + if (offset) { + numBlocks = ceil((float)n / THREADS_PER_BLOCK); + kernAddConstant<<>>(n, offset, dev_odata); + } + } + + /** + * Performs stream compaction on idata, storing the result into odata. + * All zeroes are discarded. + * + * @param n The number of elements in idata. + * @param odata The array into which to store elements. + * @param idata The array of elements to compact. + * @returns The number of elements remaining after compaction. + */ + void sort(int n, int* odata, const int* idata) { + + + int paddedN = 1 << ilog2ceil(n); + int* dev_odata1; + int* dev_odata2; + int* swp; // for ping-ponging odatas + int* dev_bitIsOne; + int* dev_bitIsZero; + int* dev_indicesZero; + int* dev_indicesOne; + + cudaMalloc((void**)&dev_odata1, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_odata2, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_bitIsOne, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_bitIsZero, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_indicesZero, paddedN * sizeof(int)); + cudaMalloc((void**)&dev_indicesOne, paddedN * sizeof(int)); + + cudaMemcpy(dev_odata1, idata, n * sizeof(int), cudaMemcpyHostToDevice); + + timer().startGpuTimer(); + + // The threads/blocks will change per kernel call but declare them here + int numBlocks = ceil((float)paddedN / THREADS_PER_BLOCK); + int numThreads; + for (int bitNum = 0; bitNum < sizeof(int) * 8; bitNum++) { + + // --- determine radix value --- + // in this case we check the `bitNum`-th bit and store whether it's a one or zero + // in two arrays. why two? so we can scan them both and calculate the proper index + // for each element based on its current radix + kernMapBitToBooleans << > > (paddedN, bitNum, dev_bitIsZero, dev_bitIsOne, dev_odata1); + //cudaDeviceSynchronize(); + //checkCUDAErrorFn("mapToBooleans failed", "radix.cu", 150); + + cudaMemcpy(dev_indicesZero, dev_bitIsZero, paddedN * sizeof(int), cudaMemcpyDeviceToDevice); + cudaMemcpy(dev_indicesOne, dev_bitIsOne, paddedN * sizeof(int), cudaMemcpyDeviceToDevice); + + // --- scan --- + + scanWithOffset(paddedN, dev_indicesZero); + int lastZeroIndexValue; + int lastZeroIndexBit; + cudaMemcpy(&lastZeroIndexValue, dev_indicesZero + paddedN - 1, sizeof(int), cudaMemcpyDeviceToHost); + cudaMemcpy(&lastZeroIndexBit, dev_bitIsZero + paddedN - 1, sizeof(int), cudaMemcpyDeviceToHost); + //cudaDeviceSynchronize(); + //checkCUDAErrorFn("memcopy failed", "radix.cu", 155); + scanWithOffset(paddedN, dev_indicesOne, lastZeroIndexValue + lastZeroIndexBit); + //cudaDeviceSynchronize(); + //checkCUDAErrorFn("scan failed", "radix.cu", 160); + + // --- scatter --- + // assign idata -> odata based on the indices calculated by the scan + + Common::kernScatter << > > (paddedN, dev_odata2, dev_odata1, dev_bitIsZero, dev_indicesZero); + //cudaDeviceSynchronize(); + //checkCUDAErrorFn("scatter failed", "radix.cu", 165); + Common::kernScatter << > > (paddedN, dev_odata2, dev_odata1, dev_bitIsOne, dev_indicesOne); + //cudaDeviceSynchronize(); + //checkCUDAErrorFn("scatter failed", "radix.cu", 165); + + // --- ping pong buffers --- + swp = dev_odata1; + dev_odata1 = dev_odata2; + dev_odata2 = swp; + } + + timer().endGpuTimer(); + + // copy the data back to the host + // offset by (paddedN - n) since any difference between the sizes will + // yield that many zeros at the beginning of the device array + cudaMemcpy(odata, dev_odata1 + (paddedN - n), n * sizeof(int), cudaMemcpyDeviceToHost); + //checkCUDAErrorFn("memcopy failed", "radix.cu", 185); + } + } +} diff --git a/stream_compaction/radix.h b/stream_compaction/radix.h new file mode 100644 index 0000000..aa489d9 --- /dev/null +++ b/stream_compaction/radix.h @@ -0,0 +1,11 @@ +#pragma once + +#include "common.h" + +namespace StreamCompaction { + namespace Radix { + StreamCompaction::Common::PerformanceTimer& timer(); + + void sort(int n, int *odata, const int *idata); + } +} diff --git a/stream_compaction/thrust.cu b/stream_compaction/thrust.cu index ec05030..02f8ce4 100644 --- a/stream_compaction/thrust.cu +++ b/stream_compaction/thrust.cu @@ -29,5 +29,17 @@ namespace StreamCompaction { thrust::copy(dev_odata.begin(), dev_odata.end(), odata); } + + void sort(int n, int *odata, const int *idata) { + + std::cout << std::endl; + thrust::copy(idata, idata + n, odata); + + timer().startGpuTimer(); + thrust::sort(odata, odata+n); + + timer().endGpuTimer(); + + } } } diff --git a/stream_compaction/thrust.h b/stream_compaction/thrust.h index fe98206..864c5f3 100644 --- a/stream_compaction/thrust.h +++ b/stream_compaction/thrust.h @@ -7,5 +7,6 @@ namespace StreamCompaction { StreamCompaction::Common::PerformanceTimer& timer(); void scan(int n, int *odata, const int *idata); + void sort(int n, int *odata, const int *idata); } } From 83e1c4f9c8595b81c4d9a481567b426fc894322e Mon Sep 17 00:00:00 2001 From: matt elser Date: Wed, 22 Sep 2021 23:20:58 -0400 Subject: [PATCH 15/15] added plots to readme --- README.md | 28 ++++++++++++++++++++-------- img/blocksizePlot.png | Bin 0 -> 247075 bytes img/compactPlot.png | Bin 0 -> 519484 bytes img/scanPlot.png | Bin 0 -> 630336 bytes img/sortPlot.png | Bin 0 -> 309507 bytes 5 files changed, 20 insertions(+), 8 deletions(-) create mode 100644 img/blocksizePlot.png create mode 100644 img/compactPlot.png create mode 100644 img/scanPlot.png create mode 100644 img/sortPlot.png diff --git a/README.md b/README.md index cfb4cf0..f39329a 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,8 @@ CUDA Stream Compaction * [LinkedIn](https://www.linkedin.com/in/matt-elser-97b8151ba/), [twitter](twitter.com/__mattelser__) * Tested on: Tested on: Ubuntu 20.04, i3-10100F @ 3.6GHz 16GB, GeForce 1660 Super 6GB +![timing data table](img/timingData.png) + ### Main Features This project implements an exclusive scan (performing an operation on (in this case a sum of) all previous elements along an array) and stream compaction (removing elements from an array based on a condition) using @@ -17,22 +19,27 @@ the CPU, GPU with CUDA, and the CUDA powered library `Thrust`. ### Time Comparison The test setup in `main.cpp` has been coopted to set up repeated timings to remove noise from measurements. -![timing data table](img/timingData.png) + +![scan comparison plot](img/scanPlot.png) +![compact comparison plot](img/compactPlot.png) + CPU scan and compact may be faster for smaller arrays, but the efficient GPU algorithms become more efficient -at array size 2^16^ for compact and 2^17^ for efficient scan. +at array size 2^16 for compact and 2^17 for efficient scan. ### Block Size Comparison changing the number of threads per blocks did not have a noticeable impact on timing. Minor differences are -can be seen in the tables below, but almost all are around one standard deviation of another, so this may just -be noise. -![block comparison tables](img/blockComparison.png) +can be seen in the graph below, but almost all are around one standard deviation of another, so this may just +be noise. Data was gathered by timing 100 runs of each algorithm with an array of size 2^22, see the bottom of +the readme for the data table. + +![block comparison plot](img/blocksizePlot.png) ### Known limitations -- [FIXED] The Naive implementation fails for array sizes greater than 2^25^. +- [FIXED] The Naive implementation fails for array sizes greater than 2^25. - Naive was calling an inefficient number of threads, leading to higher-than needed `threadIdx.x` values. When multiplied to get the `index` this overflowed int and yielded a negative index. Logic around indices (reasonably) assumed positive values and therefore caused an out of bounds write. -- compact scan fails for array sizes greater than 2^28^ due to running out of CPU memory on the (16Gb) test machine. +- compact scan fails for array sizes greater than 2^28 due to running out of CPU memory on the (16Gb) test machine. ### Extra Credit - Work Efficient GPU algorithms are more efficient than CPU (for large array sizes). This was achieved @@ -48,4 +55,9 @@ be noise. and non-power of two) up until 2^27, at which point the test machine runs out of memory. Radix sorting has been validated against `Thrust`'s sort (though the timing of the two are different by several orders of magnitude). The algorithm has not been optimized to use shared memory or contiguous memory reads, and would fail for arrays with - negative values. + negative values. 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