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test_v10_cuda.cu
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#include <limits>
#include "soa_v10_cuda.h"
#include <curand_kernel.h>
#include <Eigen/Core>
#include <Eigen/Geometry>
#define CUDA_UNIT_CHECK(A) CPPUNIT_ASSERT_EQUAL(cudaSuccess, A)
namespace {
// fill element
template <class T>
__host__ __device__ __forceinline__ void fillElement(T & e, size_t i) {
e.x = 11.0 * i;
e.y = 22.0 * i;
e.z = 33.0 * i;
e.colour = i;
e.value = 0x10001 * i;
e.py = &e.y;
}
// Fill up the elements of the SoA
[[maybe_unused]] __global__ void fillSoA(testSoA::SoA soa) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= soa.nElements()) return;
// compiler does not belive we can use a temporary soa[i] to store results.
// So make an lvalue.
auto e = soa[i];
fillElement(e, i);
}
// A read only decorator adding x,y,z interface to Eigen vectors
/*template <class C>
class EigenXYZW {
public:
EigenXYZW(const C &v): x(v, &C::x()), y(v, &C::y()), z(v, &C::z()), w(v, &C::w()) {}
class Accessor {
friend EigenXYZW<C>;
public:
operator C::Scalar() const { return (v_.*m_)(); }
private:
Accessor(const C& v, C::Scalar (C::Type::*m)()): v_(v), m_(m) {}
const C & v_;
C::Scalar (C::Type::*m_)();
};
Accessor x;
Accessor y;
Accessor z;
Accessor w;
};*/
// Fill elements with random data.
[[maybe_unused]] __global__ void randomFillSoA(testSoA::SoA soa, uint64_t seed) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= soa.nElements()) return;
curandState state;
curand_init(seed + i, 0, 0, &state);
soa[i].x = curand_uniform_double(&state);
soa[i].y = curand_uniform_double(&state);
soa[i].z = curand_uniform_double(&state);
soa[i].a()(0) = curand_uniform_double(&state);
soa[i].a()(1) = curand_uniform_double(&state);
soa[i].a()(2) = curand_uniform_double(&state);
soa[i].b()(0) = curand_uniform_double(&state);
soa[i].b()(1) = curand_uniform_double(&state);
soa[i].b()(2) = curand_uniform_double(&state);
}
[[maybe_unused]] __global__ void fillAoS(testSoA::AoSelement *aos, size_t nElements) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
fillElement(aos[i], i);
}
// Simple cross product for elements
template <typename T, typename T2>
[[maybe_unused]] __host__ __device__ __forceinline__ void crossProduct(T & r, const T2 & __restrict__ a, const T2 & __restrict__ b) {
r.x = a.y * b.z - a.z * b.y;
r.y = a.z * b.x - a.x * b.z;
r.z = a.x * b.y - a.y * b.x;
}
// Simple indirect cross product (SoA)
[[maybe_unused]] __global__ void indirectCrossProductSoA(testSoA::SoA r, const testSoA::SoA a, const testSoA::SoA b, size_t nElements) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
// C++ does not allow creating non-const references to temporary variables
// this workaround makes the temporary variable
auto ri = r[i];
crossProduct(ri, a[i], b[i]);
}
// Simple direct cross product (SoA)
[[maybe_unused]] __global__ void directCrossProductSoA(testSoA::SoA r, const testSoA::SoA a, const testSoA::SoA b, size_t nElements) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
r[i].x = a[i].y * b[i].z - a[i].z * b[i].y;
r[i].y = a[i].z * b[i].x - a[i].x * b[i].z;
r[i].z = a[i].x * b[i].y - a[i].y * b[i].x;
}
// Hand-made cross product as a reference (SoA)
[[maybe_unused]] __global__ void handcraftedCrossProductSoA(testSoA::SoA r, const testSoA::SoA a, const testSoA::SoA b, size_t nElements) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
r.x()[i] = a.y()[i] * b.z()[i] - a.z()[i] * b.y()[i];
r.y()[i] = a.z()[i] * b.x()[i] - a.x()[i] * b.z()[i];
r.z()[i] = a.x()[i] * b.y()[i] - a.y()[i] * b.x()[i];
}
using V3 = Eigen::Vector3d;
using DynStride = Eigen::InnerStride<Eigen::Dynamic>;
using CStride = Eigen::InnerStride<1024>;
using MapV3 = Eigen::Map<V3,0, DynStride>;
using CMapV3 = Eigen::Map<const V3,0, DynStride>;
// Eigen based cross product
[[maybe_unused]] __global__ void eigenCrossProductSoA(double* rx, const double* __restrict__ ax, const double* __restrict__ bx, size_t nElements, size_t stride) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
CMapV3 ma(ax+i, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(stride));
CMapV3 mb(bx+i, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(stride));
MapV3 mr(rx+i, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(stride));
mr = ma.cross(mb);
}
// Eigen based cross product on embedded vectors
[[maybe_unused]] __global__ void embeddedCrossProductSoA(testSoA::SoA soa) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= soa.nElements()) return;
#if 0
soa[i].r() = soa[i].a().cross(soa[i].b());
#else
using V3 = Eigen::Vector3d;
using DynStride = Eigen::InnerStride<Eigen::Dynamic>;
using CMapV3 = Eigen::Map<const V3,0, DynStride>;
const V3::Scalar * __restrict__ mad = soa[i].a().data();
const V3::Scalar * __restrict__ mbd = soa[i].b().data();
CMapV3 ma(mad, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(soa[i].a.stride()));
CMapV3 mb(mbd, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(soa[i].b.stride()));
soa[i].r = ma.cross(mb);
#endif
}
// Eigen based cross product on embedded vectors
[[maybe_unused]] __global__ void embeddedCrossProductLocalObjectSoA(std::byte * data, size_t nElements) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
bool deviceConstructor = true;
testSoA::SoA soa(deviceConstructor, data, nElements);
#if 1
soa[i].r() = soa[i].a.cross(soa[i].b);
#else
using V3 = Eigen::Vector3d;
using DynStride = Eigen::InnerStride<Eigen::Dynamic>;
using CMapV3 = Eigen::Map<const V3,0, DynStride>;
const V3::Scalar * __restrict__ mad = soa[i].a().data();
const V3::Scalar * __restrict__ mbd = soa[i].b().data();
CMapV3 ma(mad, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(soa[i].a.stride()));
CMapV3 mb(mbd, V3::RowsAtCompileTime, V3::ColsAtCompileTime, DynStride(soa[i].b.stride()));
soa[i].r() = ma.cross(mb);
#endif
}
// Simple cross product (SoA on CPU)
[[maybe_unused]] __host__ void indirectCPUcrossProductSoA(testSoA::SoA r, const testSoA::SoA a, const testSoA::SoA b, size_t nElements) {
for (size_t i =0; i< nElements; ++i) {
// This version is also affected.
auto ri = r[i];
crossProduct(ri, a[i], b[i]);
}
}
// Simple cross product (AoS)
[[maybe_unused]] __global__ void crossProductAoS(testSoA::AoSelement *r,
testSoA::AoSelement *a, testSoA::AoSelement *b, size_t nElements) {
size_t i = blockIdx.x * blockDim.x + threadIdx.x;
if (i >= nElements) return;
crossProduct(r[i], a[i], b[i]);
}
[[maybe_unused]] void hexdump(void *ptr, int buflen) {
/* From https://stackoverflow.com/a/29865 with adaptations */
unsigned char *buf = (unsigned char*)ptr;
int i, j;
for (i=0; i<buflen; i+=16) {
printf("%06x: ", i);
for (j=0; j<16; j++) {
if (i+j < buflen)
printf("%02x ", buf[i+j]);
else
printf(" ");
if ((i+j) % 4 == 3) printf (" ");
}
printf(" ");
// for (j=0; j<16; j++)
// if (i+j < buflen)
// printf("%c", isprint(buf[i+j]) ? buf[i+j] : '.');
printf("\n");
}
}
// Check we find what we wanted to initialize.
// Pass should be initialized to true.
template <class T>
[[maybe_unused]] __host__ __device__ __forceinline__ void checkSoAelement(T soa, size_t i, bool & pass) {
if (i >= soa.nElements() || !pass) return;
if (soa[i].x != 11.0 * i) { pass = false; return; }
if (soa[i].y != 22.0 * i) { pass = false; return; }
if (soa[i].z != 33.0 * i) { pass = false; return; }
if (soa[i].colour != i) { pass = false; return; }
if (soa[i].value != static_cast<int32_t>(0x10001 * i)) { pass = false; return; }
}
// Check r[i].{x, y, z} are close enough to zero compared to a[i].{x,y,z} and b[i].{x,y,z}
// to validate a cross product of a vector with itself produced a zero (enough) result.
template <class T>
[[maybe_unused]] __host__ __device__ __forceinline__ void checkSoAelementNullityRealtiveToSquare(T resSoA, T referenceSoA, size_t i, double epsilon, bool & pass) {
if (i >= resSoA.nElements() || !pass) return;
auto ref = max (abs(referenceSoA[i].x),
max(abs(referenceSoA[i].y),
abs(referenceSoA[i].z)));
ref *= ref * epsilon;
if (abs(resSoA[i].x) > ref) { pass = false; return; }
if (abs(resSoA[i].y) > ref) { pass = false; return; }
if (abs(resSoA[i].z) > ref) { pass = false; return; }
}
// Check r[i].{x, y, z} are close enough to zero compared to a[i].{x,y,z} and b[i].{x,y,z}
// to validate a cross product of a vector with itself produced a zero (enough) result.
template <class T>
[[maybe_unused]] __host__ __device__ __forceinline__ void checkCrossProduct(T resultSoA, T aSoA, T bSoA, size_t i, double epsilon, bool & pass) {
if (i >= resultSoA.nElements() || !pass) return;
auto refA = max (abs(aSoA[i].x),
max(abs(aSoA[i].y),
abs(aSoA[i].z)));
auto refB = max (abs(bSoA[i].x),
max(abs(bSoA[i].y),
abs(bSoA[i].z)));
auto ref = max(refA, refB);
ref *= ref * epsilon;
testSoA::AoSelement myRes;
crossProduct(myRes, aSoA[i], bSoA[i]);
if (abs(myRes.x - resultSoA[i].x) > ref) { pass = false; return; }
if (abs(myRes.y - resultSoA[i].y) > ref) { pass = false; return; }
if (abs(myRes.z - resultSoA[i].z) > ref) { pass = false; return; }
}
template <class T>
[[maybe_unused]] __host__ __device__ __forceinline__ void checkEmbeddedCrossProduct(T soa, size_t i, double epsilon, bool & pass) {
if (i >= soa.nElements() || !pass) return;
auto & a = soa[i].a();
auto & b = soa[i].b();
auto & r = soa[i].r();
auto refA = max (abs(a.x()), max(abs(a.y()), abs(a.z())));
auto refB = max (abs(b.x()), max(abs(b.y()), abs(b.z())));
auto ref = max(refA, refB);
ref *= ref * epsilon;
testSoA::AoSelement myRes, AoSa, AoSb;
AoSa.x = a.x();
AoSa.y = a.y();
AoSa.z = a.z();
AoSb.x = b.x();
AoSb.y = b.y();
AoSb.z = b.z();
crossProduct(myRes, AoSa, AoSb);
if (abs(myRes.x - r.x()) > ref) { pass = false; return; }
if (abs(myRes.y - r.y()) > ref) { pass = false; return; }
if (abs(myRes.z - r.z()) > ref) { pass = false; return; }
}
class StreamTimer {
public:
StreamTimer() {
if (cudaSuccess != cudaEventCreate(&beginning_)
|| cudaSuccess != cudaEventCreate(&end_))
throw std::bad_alloc();
}
~StreamTimer() {
cudaEventDestroy(beginning_);
cudaEventDestroy(end_);
}
void start(cudaStream_t s) {
CUDA_UNIT_CHECK(cudaEventRecord(beginning_, s));
}
void stop(cudaStream_t s) {
CUDA_UNIT_CHECK(cudaEventRecord(end_, s));
}
float mSecs() {
CUDA_UNIT_CHECK(cudaEventSynchronize(beginning_));
CUDA_UNIT_CHECK(cudaEventSynchronize(end_));
float ret;
CUDA_UNIT_CHECK(cudaEventElapsedTime(&ret, beginning_, end_));
return ret;
}
private:
cudaEvent_t beginning_, end_;
};
} // Anonymous namesapce
void testSoA::fill() {
// Get device, stream, memory
cudaDeviceProp deviceProperties;
int deviceCount=0;
CUDA_UNIT_CHECK(cudaGetDeviceCount(&deviceCount));
CPPUNIT_ASSERT(deviceCount > 0);
CUDA_UNIT_CHECK(cudaGetDeviceProperties(&deviceProperties, defaultDevice));
CUDA_UNIT_CHECK(cudaSetDevice(defaultDevice));
cudaStream_t stream;
auto e = cudaStreamCreate(&stream);
CUDA_UNIT_CHECK(cudaStreamCreate(&stream));
// Allocate memory and populate SoA descriptors
auto deviceSoABlock = make_device_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlock = make_host_unique(SoA::computeDataSize(elementsCount));
SoA deviceSoA(deviceSoABlock.get(), elementsCount);
SoA hostSoA(hostSoABlock.get(), elementsCount);
// Call kernel, get result
fillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, stream>>>(deviceSoA);
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlock.get(), deviceSoABlock.get(), SoA::computeDataSize(hostSoA.nElements()), cudaMemcpyDeviceToHost, stream));
CUDA_UNIT_CHECK(cudaStreamSynchronize(stream));
// Validate result
bool pass = true;
size_t i = 0;
for (; pass && i< hostSoA.nElements(); i++) checkSoAelement(hostSoA, i, pass);
if (!pass) {
std::cout << "In " << typeid(*this).name() << " check failed at i= " << i << ")" << std::endl;
hexdump(hostSoABlock.get(), SoA::computeDataSize(hostSoA.nElements()));
printf("base=%p, &y=%p\n", deviceSoABlock.get(), deviceSoA.y());
}
CPPUNIT_ASSERT(pass);
}
void testSoA::randomFill() {
// Get device, stream, memory
cudaDeviceProp deviceProperties;
int deviceCount=0;
CUDA_UNIT_CHECK(cudaGetDeviceCount(&deviceCount));
CPPUNIT_ASSERT(deviceCount > 0);
CUDA_UNIT_CHECK(cudaGetDeviceProperties(&deviceProperties, defaultDevice));
CUDA_UNIT_CHECK(cudaSetDevice(defaultDevice));
cudaStream_t stream;
auto e = cudaStreamCreate(&stream);
CUDA_UNIT_CHECK(cudaStreamCreate(&stream));
// Allocate memory and populate SoA descriptors
auto deviceSoABlock = make_device_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlock = make_host_unique(SoA::computeDataSize(elementsCount));
SoA deviceSoA(deviceSoABlock.get(), elementsCount);
SoA hostSoA(hostSoABlock.get(), elementsCount);
// Call kernel, get result
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, stream>>>(deviceSoA, 0xbaddeed5);
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlock.get(), deviceSoABlock.get(), SoA::computeDataSize(hostSoA.nElements()), cudaMemcpyDeviceToHost, stream));
CUDA_UNIT_CHECK(cudaStreamSynchronize(stream));
}
void testSoA::crossProduct() {
// Get device, stream, memory
cudaDeviceProp deviceProperties;
int deviceCount=0;
CUDA_UNIT_CHECK(cudaGetDeviceCount(&deviceCount));
CPPUNIT_ASSERT(deviceCount > 0);
CUDA_UNIT_CHECK(cudaGetDeviceProperties(&deviceProperties, defaultDevice));
cudaStream_t stream;
CUDA_UNIT_CHECK(cudaStreamCreate(&stream));
// Allocate memory and populate SoA descriptors (device A as source and R as result of cross product)
auto deviceSoABlockA = make_device_unique(SoA::computeDataSize(elementsCount));
auto deviceSoABlockR = make_device_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockA = make_host_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockR = make_host_unique(SoA::computeDataSize(elementsCount));
SoA deviceSoAA(deviceSoABlockA.get(), elementsCount);
SoA deviceSoAR(deviceSoABlockR.get(), elementsCount);
SoA hostSoAA(hostSoABlockA.get(), elementsCount);
SoA hostSoAR(hostSoABlockR.get(), elementsCount);
// Call kernels, get result. Also fill up result SoA to ensure the results go in the right place.
fillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, stream>>>(deviceSoAA);
fillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, stream>>>(deviceSoAR);
indirectCrossProductSoA<<<
(elementsCount - 1)/deviceProperties.warpSize + 1,
deviceProperties.warpSize,
0, stream
>>>(deviceSoAR, deviceSoAA, deviceSoAA, elementsCount);
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockA.get(), deviceSoABlockA.get(), SoA::computeDataSize(hostSoAA.nElements()), cudaMemcpyDeviceToHost, stream));
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockR.get(), deviceSoABlockR.get(), SoA::computeDataSize(hostSoAR.nElements()), cudaMemcpyDeviceToHost, stream));
CUDA_UNIT_CHECK(cudaStreamSynchronize(stream));
// Validate result
bool pass = true;
size_t i = 0;
for (; pass && i< hostSoAR.nElements(); i++)
checkSoAelementNullityRealtiveToSquare(hostSoAR, hostSoAA, i, std::numeric_limits<double>::epsilon(), pass);
if (!pass) {
std::cout << "In " << typeid(*this).name() << " check failed at i= " << i << ")" << std::endl;
std::cout << "result[" << i << "].x=" << hostSoAR[i].x << " .y=" << hostSoAR[i].y << " .z=" << hostSoAR[i].z << std::endl;
}
CPPUNIT_ASSERT(pass);
}
void testSoA::randomCrossProduct() {
// Get device, stream, memory
cudaDeviceProp deviceProperties;
int deviceCount=0;
CUDA_UNIT_CHECK(cudaGetDeviceCount(&deviceCount));
CPPUNIT_ASSERT(deviceCount > 0);
CUDA_UNIT_CHECK(cudaGetDeviceProperties(&deviceProperties, defaultDevice));
cudaStream_t streamA, streamB, streamR;
CUDA_UNIT_CHECK(cudaStreamCreate(&streamA));
CUDA_UNIT_CHECK(cudaStreamCreate(&streamB));
CUDA_UNIT_CHECK(cudaStreamCreate(&streamR));
// Allocate memory and populate SoA descriptors (device A as source and R as result of cross product)
auto deviceSoABlockA = make_device_unique(SoA::computeDataSize(elementsCount));
auto deviceSoABlockB = make_device_unique(SoA::computeDataSize(elementsCount));
auto deviceSoABlockR = make_device_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockA = make_host_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockB = make_host_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockR = make_host_unique(SoA::computeDataSize(elementsCount));
SoA deviceSoAA(deviceSoABlockA.get(), elementsCount);
SoA deviceSoAB(deviceSoABlockB.get(), elementsCount);
SoA deviceSoAR(deviceSoABlockR.get(), elementsCount);
SoA hostSoAA(hostSoABlockA.get(), elementsCount);
SoA hostSoAB(hostSoABlockB.get(), elementsCount);
SoA hostSoAR(hostSoABlockR.get(), elementsCount);
// Timer to measure performance
::StreamTimer timer;
// Call kernels, get result. Also fill up result SoA to ensure the results go in the right place.
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, streamA>>>(deviceSoAA, 0xdeadbeef);
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, streamB>>>(deviceSoAB, 0xcafefade);
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, streamR>>>(deviceSoAR, 0xfadedcab);
cudaEvent_t eventA, eventB;
CUDA_UNIT_CHECK(cudaEventCreate(&eventA));
CUDA_UNIT_CHECK(cudaEventCreate(&eventB));
CUDA_UNIT_CHECK(cudaEventRecord(eventA, streamA));
CUDA_UNIT_CHECK(cudaEventRecord(eventB, streamB));
CUDA_UNIT_CHECK(cudaStreamWaitEvent(streamR, eventA));
CUDA_UNIT_CHECK(cudaStreamWaitEvent(streamR, eventB));
// Run more to gather statistics
timer.start(streamR);
for (size_t i=0; i<20; ++i) {
indirectCrossProductSoA<<<
(elementsCount - 1)/deviceProperties.warpSize + 1,
deviceProperties.warpSize,
0, streamR
>>>(deviceSoAR, deviceSoAA, deviceSoAB, elementsCount);
}
timer.stop(streamR);
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockA.get(), deviceSoABlockA.get(), SoA::computeDataSize(hostSoAA.nElements()), cudaMemcpyDeviceToHost, streamA));
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockB.get(), deviceSoABlockB.get(), SoA::computeDataSize(hostSoAA.nElements()), cudaMemcpyDeviceToHost, streamB));
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockR.get(), deviceSoABlockR.get(), SoA::computeDataSize(hostSoAR.nElements()), cudaMemcpyDeviceToHost, streamR));
CUDA_UNIT_CHECK(cudaStreamSynchronize(streamR));
CUDA_UNIT_CHECK(cudaStreamSynchronize(streamA));
CUDA_UNIT_CHECK(cudaStreamSynchronize(streamB));
// Validate result
bool pass = true;
size_t i = 0;
for (; pass && i< hostSoAR.nElements(); i++) {
checkCrossProduct(hostSoAR, hostSoAA, hostSoAB, i, std::numeric_limits<double>::epsilon(), pass);
}
if (!pass) {
// Recompute the expected result
testSoA::AoSelement expected;
::crossProduct(expected, hostSoAA[i], hostSoAB[i]);
std::cout << "In " << __FUNCTION__ << " check failed at i= " << i << std::endl;
std::cout << "result= (" << hostSoAR[i].x << ", " << hostSoAR[i].y << ", " << hostSoAR[i].z << ")" << std::endl;
std::cout << "expected= (" << expected.x << ", " << expected.y << ", " << expected.z << ")" << std::endl;
std::cout << "A= (" << hostSoAA[i].x << ", " << hostSoAA[i].y << ", " << hostSoAA[i].z << ")" << std::endl;
std::cout << "B= (" << hostSoAB[i].x << ", " << hostSoAB[i].y << ", " << hostSoAB[i].z << ")" << std::endl;
}
std::cout << "indirectCrossProductSoA time=" << timer.mSecs() * 1000 << " us." << std::endl;
CPPUNIT_ASSERT(pass);
}
void testSoA::randomCrossProductEmbeddedVector() {
// Get device, stream, memory
cudaDeviceProp deviceProperties;
int deviceCount=0;
CUDA_UNIT_CHECK(cudaGetDeviceCount(&deviceCount));
CPPUNIT_ASSERT(deviceCount > 0);
CUDA_UNIT_CHECK(cudaGetDeviceProperties(&deviceProperties, defaultDevice));
cudaStream_t stream;
CUDA_UNIT_CHECK(cudaStreamCreate(&stream));
// Allocate memory and populate SoA descriptors (device A as source and R as result of cross product)
auto deviceSoABlock = make_device_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlock = make_host_unique(SoA::computeDataSize(elementsCount));
SoA deviceSoA(deviceSoABlock.get(), elementsCount);
SoA hostSoA(hostSoABlock.get(), elementsCount);
// Timer to measure performance
::StreamTimer timer, timer2;
// Call kernels, get result. Also fill up result SoA to ensure the results go in the right place.
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, stream>>>(deviceSoA, 0xdeadbeef);
// Run more to gather statistics
timer.start(stream);
for (size_t i=0; i<20; ++i) {
embeddedCrossProductLocalObjectSoA<<<
(elementsCount - 1)/deviceProperties.warpSize + 1,
deviceProperties.warpSize,
0, stream
>>>(deviceSoABlock.get(), elementsCount);
}
timer.stop(stream);
timer2.start(stream);
for (size_t i=0; i<20; ++i) {
embeddedCrossProductSoA<<<
(elementsCount - 1)/deviceProperties.warpSize + 1,
deviceProperties.warpSize,
0, stream
>>>(deviceSoA);
}
timer2.stop(stream);
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlock.get(), deviceSoABlock.get(), SoA::computeDataSize(hostSoA.nElements()), cudaMemcpyDeviceToHost, stream));
CUDA_UNIT_CHECK(cudaStreamSynchronize(stream));
// Validate result
bool pass = true;
size_t i = 0;
for (; pass && i< hostSoA.nElements(); i++) {
checkEmbeddedCrossProduct(hostSoA, i, std::numeric_limits<double>::epsilon(), pass);
}
if (!pass) {
// Recompute the expected result
Eigen::Vector3d expected;
auto a = hostSoA[i].a();
auto b = hostSoA[i].b();
auto r = hostSoA[i].r();
expected = a.cross(b);
std::cout << "In " << __FUNCTION__ << " check failed at i= " << i << std::endl;
std::cout << "result= (" << r.x() << ", " << r.y() << ", " << r.z() << ")" << std::endl;
std::cout << "expected= (" << expected.x() << ", " << expected.y() << ", " << expected.z() << ")" << std::endl;
std::cout << "A= (" << a.x() << ", " << a.y() << ", " << a.z() << ")" << std::endl;
std::cout << "B= (" << b.x() << ", " << b.y() << ", " << b.z() << ")" << std::endl;
}
std::cout << "embeddedCrossProductLocalObjectSoA time=" << timer.mSecs() * 1000 << " us." << std::endl;
std::cout << "embeddedCrossProductSoA time=" << timer2.mSecs() * 1000 << " us." << std::endl;
CPPUNIT_ASSERT(pass);
}
void testSoA::randomCrossProductEigen() {
// Get device, stream, memory
cudaDeviceProp deviceProperties;
int deviceCount=0;
CUDA_UNIT_CHECK(cudaGetDeviceCount(&deviceCount));
CPPUNIT_ASSERT(deviceCount > 0);
CUDA_UNIT_CHECK(cudaGetDeviceProperties(&deviceProperties, defaultDevice));
cudaStream_t streamA, streamB, streamR;
CUDA_UNIT_CHECK(cudaStreamCreate(&streamA));
CUDA_UNIT_CHECK(cudaStreamCreate(&streamB));
CUDA_UNIT_CHECK(cudaStreamCreate(&streamR));
// Allocate memory and populate SoA descriptors (device A as source and R as result of cross product)
auto deviceSoABlockA = make_device_unique(SoA::computeDataSize(elementsCount));
auto deviceSoABlockB = make_device_unique(SoA::computeDataSize(elementsCount));
auto deviceSoABlockR = make_device_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockA = make_host_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockB = make_host_unique(SoA::computeDataSize(elementsCount));
auto hostSoABlockR = make_host_unique(SoA::computeDataSize(elementsCount));
SoA deviceSoAA(deviceSoABlockA.get(), elementsCount);
SoA deviceSoAB(deviceSoABlockB.get(), elementsCount);
SoA deviceSoAR(deviceSoABlockR.get(), elementsCount);
SoA hostSoAA(hostSoABlockA.get(), elementsCount);
SoA hostSoAB(hostSoABlockB.get(), elementsCount);
SoA hostSoAR(hostSoABlockR.get(), elementsCount);
// Timer to measure performance
::StreamTimer timer;
// Call kernels, get result. Also fill up result SoA to ensure the results go in the right place.
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, streamA>>>(deviceSoAA, 0xdeadbeef);
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, streamB>>>(deviceSoAB, 0xcafefade);
randomFillSoA<<<(elementsCount - 1)/deviceProperties.warpSize + 1, deviceProperties.warpSize, 0, streamR>>>(deviceSoAR, 0xfadedcab);
cudaEvent_t eventA, eventB;
CUDA_UNIT_CHECK(cudaEventCreate(&eventA));
CUDA_UNIT_CHECK(cudaEventCreate(&eventB));
CUDA_UNIT_CHECK(cudaEventRecord(eventA, streamA));
CUDA_UNIT_CHECK(cudaEventRecord(eventB, streamB));
CUDA_UNIT_CHECK(cudaStreamWaitEvent(streamR, eventA));
CUDA_UNIT_CHECK(cudaStreamWaitEvent(streamR, eventB));
const size_t stride = (((elementsCount * sizeof(double) - 1) / deviceSoAA.byteAlignment() ) + 1) * deviceSoAA.byteAlignment() / sizeof(double);
// Run more to gather statistics
timer.start(streamR);
for (size_t i=0; i<20; ++i) {
eigenCrossProductSoA<<<
(elementsCount - 1)/deviceProperties.warpSize + 1,
deviceProperties.warpSize,
0, streamR
>>>(deviceSoAR.x(), deviceSoAA.x(), deviceSoAB.x(), elementsCount, stride);
}
timer.stop(streamR);
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockA.get(), deviceSoABlockA.get(), SoA::computeDataSize(hostSoAA.nElements()), cudaMemcpyDeviceToHost, streamA));
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockB.get(), deviceSoABlockB.get(), SoA::computeDataSize(hostSoAA.nElements()), cudaMemcpyDeviceToHost, streamB));
CUDA_UNIT_CHECK(cudaMemcpyAsync(hostSoABlockR.get(), deviceSoABlockR.get(), SoA::computeDataSize(hostSoAR.nElements()), cudaMemcpyDeviceToHost, streamR));
CUDA_UNIT_CHECK(cudaStreamSynchronize(streamR));
CUDA_UNIT_CHECK(cudaStreamSynchronize(streamA));
CUDA_UNIT_CHECK(cudaStreamSynchronize(streamB));
// Validate result
bool pass = true;
size_t i = 0;
for (; pass && i< hostSoAR.nElements(); i++) {
checkCrossProduct(hostSoAR, hostSoAA, hostSoAB, i, std::numeric_limits<double>::epsilon(), pass);
}
if (!pass) {
// Recompute the expected result
testSoA::AoSelement expected;
::crossProduct(expected, hostSoAA[i], hostSoAB[i]);
std::cout << "In " << __FUNCTION__ << " check failed at i= " << i << std::endl;
std::cout << "result= (" << hostSoAR[i].x << ", " << hostSoAR[i].y << ", " << hostSoAR[i].z << ")" << std::endl;
std::cout << "expected= (" << expected.x << ", " << expected.y << ", " << expected.z << ")" << std::endl;
std::cout << "A= (" << hostSoAA[i].x << ", " << hostSoAA[i].y << ", " << hostSoAA[i].z << ")" << std::endl;
std::cout << "B= (" << hostSoAB[i].x << ", " << hostSoAB[i].y << ", " << hostSoAB[i].z << ")" << std::endl;
}
std::cout << "eigenCrossProductSoA time=" << timer.mSecs() * 1000 << " us." << std::endl;
CPPUNIT_ASSERT(pass);
}