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For histograms, opting into maximum shared memory available per block. (#5491)

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Andy Adinets 2020-04-21 04:56:42 +02:00 committed by GitHub
parent 9c1103e06c
commit 73142041b9
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 54 additions and 31 deletions
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19
src/common/device_helpers.cuh
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@ -100,7 +100,7 @@ inline size_t TotalMemory(int device_idx) {
}
/**
* \fn inline int max_shared_memory(int device_idx)
* \fn inline int MaxSharedMemory(int device_idx)
*
* \brief Maximum shared memory per block on this device.
*
@ -113,6 +113,23 @@ inline size_t MaxSharedMemory(int device_idx) {
return prop.sharedMemPerBlock;
}
/**
* \fn inline int MaxSharedMemoryOptin(int device_idx)
*
* \brief Maximum dynamic shared memory per thread block on this device
that can be opted into when using cudaFuncSetAttribute().
*
* \param device_idx Zero-based index of the device.
*/
inline size_t MaxSharedMemoryOptin(int device_idx) {
int max_shared_memory = 0;
dh::safe_cuda(cudaDeviceGetAttribute
(&max_shared_memory, cudaDevAttrMaxSharedMemoryPerBlockOptin,
device_idx));
return size_t(max_shared_memory);
}
inline void CheckComputeCapability() {
for (int d_idx = 0; d_idx < xgboost::common::AllVisibleGPUs(); ++d_idx) {
cudaDeviceProp prop;

45
src/tree/gpu_hist/histogram.cu
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@ -150,21 +150,37 @@ void BuildGradientHistogram(EllpackDeviceAccessor const& matrix,
common::Span<GradientPair const> gpair,
common::Span<const uint32_t> d_ridx,
common::Span<GradientSumT> histogram,
GradientSumT rounding, bool shared) {
const size_t smem_size =
shared
? sizeof(GradientSumT) * matrix.NumBins()
: 0;
auto n_elements = d_ridx.size() * matrix.row_stride;
GradientSumT rounding) {
// decide whether to use shared memory
int device = 0;
dh::safe_cuda(cudaGetDevice(&device));
int max_shared_memory = dh::MaxSharedMemoryOptin(device);
size_t smem_size = sizeof(GradientSumT) * matrix.NumBins();
bool shared = smem_size <= max_shared_memory;
smem_size = shared ? smem_size : 0;
uint32_t items_per_thread = 8;
uint32_t block_threads = 256;
auto grid_size = static_cast<uint32_t>(
common::DivRoundUp(n_elements, items_per_thread * block_threads));
// opt into maximum shared memory for the kernel if necessary
auto kernel = SharedMemHistKernel<GradientSumT>;
if (shared) {
dh::safe_cuda(cudaFuncSetAttribute
(kernel, cudaFuncAttributeMaxDynamicSharedMemorySize,
max_shared_memory));
}
// determine the launch configuration
unsigned block_threads = shared ? 1024 : 256;
int n_mps = 0;
dh::safe_cuda(cudaDeviceGetAttribute(&n_mps, cudaDevAttrMultiProcessorCount, device));
int n_blocks_per_mp = 0;
dh::safe_cuda(cudaOccupancyMaxActiveBlocksPerMultiprocessor
(&n_blocks_per_mp, kernel, block_threads, smem_size));
unsigned grid_size = n_blocks_per_mp * n_mps;
auto n_elements = d_ridx.size() * matrix.row_stride;
dh::LaunchKernel {grid_size, block_threads, smem_size} (
SharedMemHistKernel<GradientSumT>,
matrix, d_ridx, histogram.data(), gpair.data(), n_elements,
kernel, matrix, d_ridx, histogram.data(), gpair.data(), n_elements,
rounding, shared);
dh::safe_cuda(cudaGetLastError());
}
template void BuildGradientHistogram<GradientPair>(
@ -172,13 +188,14 @@ template void BuildGradientHistogram<GradientPair>(
common::Span<GradientPair const> gpair,
common::Span<const uint32_t> ridx,
common::Span<GradientPair> histogram,
GradientPair rounding, bool shared);
GradientPair rounding);
template void BuildGradientHistogram<GradientPairPrecise>(
EllpackDeviceAccessor const& matrix,
common::Span<GradientPair const> gpair,
common::Span<const uint32_t> ridx,
common::Span<GradientPairPrecise> histogram,
GradientPairPrecise rounding, bool shared);
GradientPairPrecise rounding);
} // namespace tree
} // namespace xgboost

2
src/tree/gpu_hist/histogram.cuh
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@ -22,7 +22,7 @@ void BuildGradientHistogram(EllpackDeviceAccessor const& matrix,
common::Span<GradientPair const> gpair,
common::Span<const uint32_t> ridx,
common::Span<GradientSumT> histogram,
GradientSumT rounding, bool shared);
GradientSumT rounding);
} // namespace tree
} // namespace xgboost

12
src/tree/updater_gpu_hist.cu
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@ -422,7 +422,6 @@ struct GPUHistMakerDevice {
TrainParam param;
bool deterministic_histogram;
bool use_shared_memory_histograms {false};
GradientSumT histogram_rounding;
@ -596,7 +595,7 @@ struct GPUHistMakerDevice {
auto d_node_hist = hist.GetNodeHistogram(nidx);
auto d_ridx = row_partitioner->GetRows(nidx);
BuildGradientHistogram(page->GetDeviceAccessor(device_id), gpair, d_ridx, d_node_hist,
histogram_rounding, use_shared_memory_histograms);
histogram_rounding);
}
void SubtractionTrick(int nidx_parent, int nidx_histogram,
@ -910,15 +909,6 @@ inline void GPUHistMakerDevice<GradientSumT>::InitHistogram() {
host_node_sum_gradients.resize(param.MaxNodes());
node_sum_gradients.resize(param.MaxNodes());
// check if we can use shared memory for building histograms
// (assuming atleast we need 2 CTAs per SM to maintain decent latency
// hiding)
auto histogram_size = sizeof(GradientSumT) * page->Cuts().TotalBins();
auto max_smem = dh::MaxSharedMemory(device_id);
if (histogram_size <= max_smem) {
use_shared_memory_histograms = true;
}
// Init histogram
hist.Init(device_id, page->Cuts().TotalBins());
}

6
tests/cpp/tree/gpu_hist/test_histogram.cu
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@ -27,7 +27,7 @@ void TestDeterminsticHistogram() {
auto rounding = CreateRoundingFactor<Gradient>(gpair.DeviceSpan());
BuildGradientHistogram(page->GetDeviceAccessor(0), gpair.DeviceSpan(), ridx,
d_histogram, rounding, true);
d_histogram, rounding);
for (size_t i = 0; i < kRounds; ++i) {
dh::device_vector<Gradient> new_histogram(kBins * kCols);
@ -35,7 +35,7 @@ void TestDeterminsticHistogram() {
auto rounding = CreateRoundingFactor<Gradient>(gpair.DeviceSpan());
BuildGradientHistogram(page->GetDeviceAccessor(0), gpair.DeviceSpan(), ridx,
d_histogram, rounding, true);
d_histogram, rounding);
for (size_t j = 0; j < new_histogram.size(); ++j) {
ASSERT_EQ(((Gradient)new_histogram[j]).GetGrad(),
@ -50,7 +50,7 @@ void TestDeterminsticHistogram() {
gpair.SetDevice(0);
dh::device_vector<Gradient> baseline(kBins * kCols);
BuildGradientHistogram(page->GetDeviceAccessor(0), gpair.DeviceSpan(), ridx,
dh::ToSpan(baseline), rounding, true);
dh::ToSpan(baseline), rounding);
for (size_t i = 0; i < baseline.size(); ++i) {
EXPECT_NEAR(((Gradient)baseline[i]).GetGrad(), ((Gradient)histogram[i]).GetGrad(),
((Gradient)baseline[i]).GetGrad() * 1e-3);

1
tests/cpp/tree/test_gpu_hist.cu
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@ -101,7 +101,6 @@ void TestBuildHist(bool use_shared_memory_histograms) {
maker.hist.AllocateHistogram(0);
maker.gpair = gpair.DeviceSpan();
maker.use_shared_memory_histograms = use_shared_memory_histograms;
maker.BuildHist(0);
DeviceHistogram<GradientSumT> d_hist = maker.hist;