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Extract partial sum into an independent algorithm.
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trivialfis committed May 12, 2022
1 parent 7ef54e3 commit 2565432
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Showing 7 changed files with 137 additions and 68 deletions.
18 changes: 0 additions & 18 deletions src/common/common.h
Expand Up @@ -274,24 +274,6 @@ template <typename Indexable>
XGBOOST_DEVICE size_t LastOf(size_t group, Indexable const &indptr) {
return indptr[group + 1] - 1;
}

/**
* \brief Run length encode on CPU, input must be sorted.
*/
template <typename Iter, typename Idx>
void RunLengthEncode(Iter begin, Iter end, std::vector<Idx> *p_out) {
auto &out = *p_out;
out = std::vector<Idx>{0};
size_t n = std::distance(begin, end);
for (size_t i = 1; i < n; ++i) {
if (begin[i] != begin[i - 1]) {
out.push_back(i);
}
}
if (out.back() != n) {
out.push_back(n);
}
}
} // namespace common
} // namespace xgboost
#endif // XGBOOST_COMMON_COMMON_H_
95 changes: 95 additions & 0 deletions src/common/numeric.h
@@ -0,0 +1,95 @@
/*!
* Copyright 2022, XGBoost contributors.
*/
#ifndef XGBOOST_COMMON_NUMERIC_H_
#define XGBOOST_COMMON_NUMERIC_H_

#include <iterator> // std::iterator_traits
#include <vector>

#include "threading_utils.h"
#include "xgboost/generic_parameters.h"

namespace xgboost {
namespace common {

/**
* \brief Run length encode on CPU, input must be sorted.
*/
template <typename Iter, typename Idx>
void RunLengthEncode(Iter begin, Iter end, std::vector<Idx> *p_out) {
auto &out = *p_out;
out = std::vector<Idx>{0};
size_t n = std::distance(begin, end);
for (size_t i = 1; i < n; ++i) {
if (begin[i] != begin[i - 1]) {
out.push_back(i);
}
}
if (out.back() != n) {
out.push_back(n);
}
}

/**
* \brief Varient of std::partial_sum, out_it should point to a container that has n + 1
* elements. Useful for constructing a CSR indptr.
*/
template <typename InIt, typename OutIt, typename T>
void PartialSum(int32_t n_threads, InIt begin, InIt end, T init, OutIt out_it) {
static_assert(std::is_same<T, typename std::iterator_traits<InIt>::value_type>::value, "");
static_assert(std::is_same<T, typename std::iterator_traits<OutIt>::value_type>::value, "");
// The number of threads is pegged to the batch size. If the OMP block is parallelized
// on anything other than the batch/block size, it should be reassigned
auto n = static_cast<size_t>(std::distance(begin, end));
const size_t batch_threads =
std::max(static_cast<size_t>(1), std::min(n, static_cast<size_t>(n_threads)));
common::MemStackAllocator<T, 128> partial_sums(batch_threads);

size_t block_size = n / batch_threads;

dmlc::OMPException exc;
#pragma omp parallel num_threads(batch_threads)
{
#pragma omp for
for (omp_ulong tid = 0; tid < batch_threads; ++tid) {
exc.Run([&]() {
size_t ibegin = block_size * tid;
size_t iend = (tid == (batch_threads - 1) ? n : (block_size * (tid + 1)));

T running_sum = 0;
for (size_t ridx = ibegin; ridx < iend; ++ridx) {
running_sum += *(begin + ridx);
*(out_it + 1 + ridx) = running_sum;
}
});
}

#pragma omp single
{
exc.Run([&]() {
partial_sums[0] = init;
for (size_t i = 1; i < batch_threads; ++i) {
partial_sums[i] = partial_sums[i - 1] + *(out_it + i * block_size);
}
});
}

#pragma omp for
for (omp_ulong tid = 0; tid < batch_threads; ++tid) {
exc.Run([&]() {
size_t ibegin = block_size * tid;
size_t iend = (tid == (batch_threads - 1) ? n : (block_size * (tid + 1)));

for (size_t i = ibegin; i < iend; ++i) {
*(out_it + 1 + i) += partial_sums[tid];
}
});
}
}
exc.Rethrow();
}
} // namespace common
} // namespace xgboost

#endif // XGBOOST_COMMON_NUMERIC_H_
1 change: 1 addition & 0 deletions src/data/data.cc
Expand Up @@ -21,6 +21,7 @@
#include "../common/io.h"
#include "../common/linalg_op.h"
#include "../common/math.h"
#include "../common/numeric.h"
#include "../common/version.h"
#include "../common/group_data.h"
#include "../common/threading_utils.h"
Expand Down
56 changes: 6 additions & 50 deletions src/data/gradient_index.cc
Expand Up @@ -10,6 +10,7 @@

#include "../common/column_matrix.h"
#include "../common/hist_util.h"
#include "../common/numeric.h"
#include "../common/threading_utils.h"

namespace xgboost {
Expand All @@ -28,58 +29,13 @@ void GHistIndexMatrix::PushBatch(SparsePage const &batch,
common::Span<FeatureType const> ft,
size_t rbegin, size_t prev_sum, uint32_t nbins,
int32_t n_threads) {
// The number of threads is pegged to the batch size. If the OMP
// block is parallelized on anything other than the batch/block size,
// it should be reassigned
auto page = batch.GetView();
auto it = common::MakeIndexTransformIter([&](size_t ridx) { return page[ridx].size(); });
common::PartialSum(n_threads, it, it + page.Size(), prev_sum, row_ptr.begin() + rbegin);
// The number of threads is pegged to the batch size. If the OMP block is parallelized
// on anything other than the batch/block size, it should be reassigned
const size_t batch_threads =
std::max(static_cast<size_t>(1), std::min(batch.Size(), static_cast<size_t>(n_threads)));
auto page = batch.GetView();
common::MemStackAllocator<size_t, 128> partial_sums(batch_threads);

size_t block_size = batch.Size() / batch_threads;

dmlc::OMPException exc;
#pragma omp parallel num_threads(batch_threads)
{
#pragma omp for
for (omp_ulong tid = 0; tid < batch_threads; ++tid) {
exc.Run([&]() {
size_t ibegin = block_size * tid;
size_t iend = (tid == (batch_threads - 1) ? batch.Size()
: (block_size * (tid + 1)));

size_t running_sum = 0;
for (size_t ridx = ibegin; ridx < iend; ++ridx) {
running_sum += page[ridx].size();
row_ptr[rbegin + 1 + ridx] = running_sum;
}
});
}

#pragma omp single
{
exc.Run([&]() {
partial_sums[0] = prev_sum;
for (size_t i = 1; i < batch_threads; ++i) {
partial_sums[i] = partial_sums[i - 1] + row_ptr[rbegin + i * block_size];
}
});
}

#pragma omp for
for (omp_ulong tid = 0; tid < batch_threads; ++tid) {
exc.Run([&]() {
size_t ibegin = block_size * tid;
size_t iend = (tid == (batch_threads - 1) ? batch.Size()
: (block_size * (tid + 1)));

for (size_t i = ibegin; i < iend; ++i) {
row_ptr[rbegin + 1 + i] += partial_sums[tid];
}
});
}
}
exc.Rethrow();

const size_t n_index = row_ptr[rbegin + batch.Size()]; // number of entries in this page
ResizeIndex(n_index, isDense_);
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1 change: 1 addition & 0 deletions src/objective/adaptive.cc
Expand Up @@ -7,6 +7,7 @@
#include <vector>

#include "../common/common.h"
#include "../common/numeric.h"
#include "../common/stats.h"
#include "../common/threading_utils.h"
#include "xgboost/tree_model.h"
Expand Down
33 changes: 33 additions & 0 deletions tests/cpp/common/test_numeric.cc
@@ -0,0 +1,33 @@
/*!
* Copyright 2022, XGBoost contributors.
*/
#include <gtest/gtest.h>

#include <numeric>

#include "../../../src/common/numeric.h"

namespace xgboost {
namespace common {
TEST(Numeric, PartialSum) {
{
std::vector<size_t> values{1, 2, 3, 4};
std::vector<size_t> result(values.size() + 1);
Context ctx;
PartialSum(ctx.Threads(), values.begin(), values.end(), static_cast<size_t>(0), result.begin());
std::vector<size_t> sol(values.size() + 1, 0);
std::partial_sum(values.begin(), values.end(), sol.begin() + 1);
ASSERT_EQ(sol, result);
}
{
std::vector<double> values{1.5, 2.5, 3.5, 4.5};
std::vector<double> result(values.size() + 1);
Context ctx;
PartialSum(ctx.Threads(), values.begin(), values.end(), 0.0, result.begin());
std::vector<double> sol(values.size() + 1, 0.0);
std::partial_sum(values.begin(), values.end(), sol.begin() + 1);
ASSERT_EQ(sol, result);
}
}
} // namespace common
} // namespace xgboost
1 change: 1 addition & 0 deletions tests/cpp/tree/test_approx.cc
Expand Up @@ -3,6 +3,7 @@
*/
#include <gtest/gtest.h>

#include "../../../src/common/numeric.h"
#include "../../../src/tree/updater_approx.h"
#include "../helpers.h"
#include "test_partitioner.h"
Expand Down

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