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rocm-systems/tests/performance/stream/hipPerfDeviceConcurrency.cpp
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TomSang 9035ae3154 SWDEV-299773 - Enable performance tests on NV (#2337)
1. Simply enable test on NV
   Some need minor fix
performance/compute/hipPerfDotProduct.cpp
performance/dispatch/hipPerfDispatchSpeed.cpp
performance/memory/hipPerfBufferCopyRectSpeed.cpp
performance/memory/hipPerfBufferCopySpeed.cpp
performance/memory/hipPerfDevMemReadSpeed.cpp
performance/memory/hipPerfDevMemWriteSpeed.cpp
performance/memory/hipPerfMemcpy.cpp
performance/memory/hipPerfMemset.cpp
performance/memory/hipPerfSharedMemReadSpeed.cpp
performance/stream/hipPerfDeviceConcurrency.cpp
performance/stream/hipPerfStreamCreateCopyDestroy.cpp

2. Enable and fix on NV
performance/compute/hipPerfMandelbrot.cpp
   Root cause: coordIdx is random
   Solution: Initialize coordIdx correctly
performance/memory/hipPerfMemFill.cpp
   Root cause: Hip ext Apis called.
   Solution: Exclude case with Hip ext Apis involved
performance/memory/hipPerfMemMallocCpyFree.cpp
   Root cause: Test allocates device memory more than GPU has.
   Solution: Allocate device memory in terms of GPU capacity.
tests/performance/memory/hipPerfSampleRate.cpp
   Root cause: Cuda has no operators += for float2 and float4.
   Solution: Provide the operators.
performance/stream/hipPerfStreamConcurrency.cpp
   Root cause:float4 format doesn't match cude.
              operators are missing in cuda lib.
   Solution: Use (x, y, z, w) format.
             Add necessary float4 operatoris for cuda.

Change-Id: I5add29ebabcfb21fb3ef89d09004c5d13423a291
2021-09-14 13:37:13 +05:30

285 linhas
7.3 KiB
C++

/*
Copyright (c) 2015 - 2021 Advanced Micro Devices, Inc. All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*/
/* HIT_START
* BUILD: %t %s ../../src/test_common.cpp
* TEST: %t
* HIT_END
*/
#include <iostream>
#include <chrono>
#include "test_common.h"
typedef struct {
double x;
double y;
double width;
} coordRec;
static coordRec coords[] = {
{0.0, 0.0, 0.00001}, // All black
};
static unsigned int numCoords = sizeof(coords) / sizeof(coordRec);
__global__ void mandelbrot(uint *out, uint width, float xPos, float yPos, float xStep,
float yStep, uint maxIter) {
int tid = (blockIdx.x * blockDim.x + threadIdx.x);
int i = tid % width;
int j = tid / width;
float x0 = (float)(xPos + xStep*i);
float y0 = (float)(yPos + yStep*j);
float x = x0;
float y = y0;
uint iter = 0;
float tmp;
for (iter = 0; (x*x + y*y <= 4.0f) && (iter < maxIter); iter++) {
tmp = x;
x = fma(-y,y,fma(x,x,x0));
y = fma(2.0f*tmp,y,y0);
}
out[tid] = iter;
};
class hipPerfDeviceConcurrency {
public:
hipPerfDeviceConcurrency();
~hipPerfDeviceConcurrency();
void setNumGpus(unsigned int num) {
numDevices = num;
}
unsigned int getNumGpus() {
return numDevices;
}
void open(void);
void close(void);
void run(unsigned int testCase, int numGpus);
private:
void setData(void *ptr, unsigned int value);
void checkData(uint *ptr);
unsigned int numDevices;
unsigned int width_;
unsigned int bufSize;
unsigned int coordIdx;
unsigned long long totalIters = 0;
};
hipPerfDeviceConcurrency::hipPerfDeviceConcurrency() {}
hipPerfDeviceConcurrency::~hipPerfDeviceConcurrency() {}
void hipPerfDeviceConcurrency::open(void) {
int nGpu = 0;
HIPCHECK(hipGetDeviceCount(&nGpu));
setNumGpus(nGpu);
if (nGpu < 1) {
failed("No GPU!");
}
}
void hipPerfDeviceConcurrency::close() {
}
void hipPerfDeviceConcurrency::run(unsigned int testCase, int numGpus) {
static int deviceId;
uint * hPtr[numGpus];
uint * dPtr[numGpus];
hipStream_t streams[numGpus];
int numCUs[numGpus];
unsigned int maxIter[numGpus];
unsigned long long expectedIters[numGpus];
int threads, threads_per_block, blocks;
float xStep, yStep, xPos, yPos;
for(int i = 0; i < numGpus; i++) {
if(testCase != 0) {
deviceId = i;
}
HIPCHECK(hipSetDevice(deviceId));
hipDeviceProp_t props = {0};
HIPCHECK(hipGetDeviceProperties(&props, i));
if (testCase != 0) {
std::cout << "info: running on bus " << "0x" << props.pciBusID << " " << props.name
<< " with " << props.multiProcessorCount << " CUs" << " and device ID: "
<< i << std::endl;
}
numCUs[i] = props.multiProcessorCount;
int clkFrequency = 0;
HIPCHECK(hipDeviceGetAttribute(&clkFrequency, hipDeviceAttributeClockRate, i));
clkFrequency =(unsigned int)clkFrequency/1000;
// Maximum iteration count
// maxIter = 8388608 * (engine_clock / 1000).serial execution
maxIter[i] = (unsigned int)(((8388608 * ((float)clkFrequency / 1000)) * numCUs[i]) / 128);
maxIter[i] = (maxIter[i] + 15) & ~15;
// Width is divisible by 4 because the mandelbrot kernel processes 4 pixels at once.
width_ = 256;
bufSize = width_ * width_ * sizeof(uint);
// Create streams for concurrency
HIPCHECK(hipStreamCreate(&streams[i]));
// Allocate memory on the host and device
HIPCHECK(hipHostMalloc((void **)&hPtr[i], bufSize, hipHostMallocDefault));
setData(hPtr[i], 0xdeadbeef);
HIPCHECK(hipMalloc((uint **)&dPtr[i], bufSize))
// Prepare kernel launch parameters
threads = (bufSize/sizeof(uint));
threads_per_block = 64;
blocks = (threads/threads_per_block) + (threads % threads_per_block);
coordIdx = testCase % numCoords;
xStep = (float)(coords[coordIdx].width / (double)width_);
yStep = (float)(-coords[coordIdx].width / (double)width_);
xPos = (float)(coords[coordIdx].x - 0.5 * coords[coordIdx].width);
yPos = (float)(coords[coordIdx].y + 0.5 * coords[coordIdx].width);
// Copy memory from host to device
HIPCHECK(hipMemcpy(dPtr[i], hPtr[i], bufSize, hipMemcpyHostToDevice));
}
// Time the kernel execution
auto all_start = std::chrono::steady_clock::now();
for(int i = 0; i < numGpus; i++) {
if(testCase != 0) {
deviceId = i;
}
HIPCHECK(hipSetDevice(deviceId));
hipLaunchKernelGGL(mandelbrot, dim3(blocks), dim3(threads_per_block), 0, streams[i],
dPtr[i], width_, xPos, yPos, xStep, yStep, maxIter[i]);
}
for(int i = 0; i < numGpus; i++) {
HIPCHECK(hipStreamSynchronize(0));
}
auto all_end = std::chrono::steady_clock::now();
std::chrono::duration<double> all_kernel_time = all_end - all_start;
for(int i = 0; i < numGpus; i++) {
if(testCase != 0) {
deviceId = i;
}
HIPCHECK(hipSetDevice(deviceId));
// Copy data back from device to the host
HIPCHECK(hipMemcpy(hPtr[i], dPtr[i], bufSize, hipMemcpyDeviceToHost));
checkData(hPtr[i]);
expectedIters[i] = width_ * width_ * (unsigned long long) maxIter[i];
if (testCase != 0) {
checkData(hPtr[i]);
if(totalIters != expectedIters[i]) {
std::cout << "Incorrect iteration count detected" << std::endl;
}
}
HIPCHECK(hipStreamDestroy(streams[i]));
// Free host and device memory
HIPCHECK(hipHostFree(hPtr[i]));
HIPCHECK(hipFree(dPtr[i]));
}
if (testCase != 0) {
std::cout << '\n' << "Measured time for kernel computation on " << numGpus << " device (s): "
<< all_kernel_time.count() << " (s) " << '\n' << std::endl;
}
if(testCase == 0) {
deviceId++;
}
}
void hipPerfDeviceConcurrency::setData(void *ptr, unsigned int value) {
unsigned int *ptr2 = (unsigned int *)ptr;
for (unsigned int i = 0; i < width_ * width_ ; i++) {
ptr2[i] = value;
}
}
void hipPerfDeviceConcurrency::checkData(uint *ptr) {
totalIters = 0;
for (unsigned int i = 0; i < width_ * width_; i++) {
totalIters += ptr[i];
}
}
int main(int argc, char* argv[]) {
hipPerfDeviceConcurrency deviceConcurrency;
deviceConcurrency.open();
int nGpu = deviceConcurrency.getNumGpus();
// testCase = 0 refers to warmup kernel run
int testCase = 0;
for (int i = 0; i < nGpu; i++) {
// Warm-up kernel on all devices
deviceConcurrency.run(testCase, 1);
}
// Time for kernel on 1 device
deviceConcurrency.run(++testCase, 1);
// Time for kernel on all available devices
deviceConcurrency.run(++testCase, nGpu);
passed();
}