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More collective aggregators (#9060)

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This commit is contained in:
Rong Ou
2023-04-21 12:32:05 -07:00
committed by GitHub
parent 7032981350
commit 8dbe0510de
11 changed files with 107 additions and 89 deletions
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16
src/objective/adaptive.h
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@@ -6,8 +6,9 @@
#include <algorithm>
#include <cstdint> // std::int32_t
#include <limits>
#include <vector> // std::vector
#include <vector> // std::vector
#include "../collective/aggregator.h"
#include "../collective/communicator-inl.h"
#include "../common/common.h"
#include "xgboost/base.h" // bst_node_t
@@ -41,10 +42,7 @@ inline void UpdateLeafValues(std::vector<float>* p_quantiles, std::vector<bst_no
auto& quantiles = *p_quantiles;
auto const& h_node_idx = nidx;
size_t n_leaf{h_node_idx.size()};
if (info.IsRowSplit()) {
collective::Allreduce<collective::Operation::kMax>(&n_leaf, 1);
}
size_t n_leaf = collective::GlobalMax(info, h_node_idx.size());
CHECK(quantiles.empty() || quantiles.size() == n_leaf);
if (quantiles.empty()) {
quantiles.resize(n_leaf, std::numeric_limits<float>::quiet_NaN());
@@ -54,16 +52,12 @@ inline void UpdateLeafValues(std::vector<float>* p_quantiles, std::vector<bst_no
std::vector<int32_t> n_valids(quantiles.size());
std::transform(quantiles.cbegin(), quantiles.cend(), n_valids.begin(),
[](float q) { return static_cast<int32_t>(!std::isnan(q)); });
if (info.IsRowSplit()) {
collective::Allreduce<collective::Operation::kSum>(n_valids.data(), n_valids.size());
}
collective::GlobalSum(info, &n_valids);
// convert to 0 for all reduce
std::replace_if(
quantiles.begin(), quantiles.end(), [](float q) { return std::isnan(q); }, 0.f);
// use the mean value
if (info.IsRowSplit()) {
collective::Allreduce<collective::Operation::kSum>(quantiles.data(), quantiles.size());
}
collective::GlobalSum(info, &quantiles);
for (size_t i = 0; i < n_leaf; ++i) {
if (n_valids[i] > 0) {
quantiles[i] /= static_cast<float>(n_valids[i]);

8
src/objective/quantile_obj.cu
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@@ -1,6 +1,7 @@
/**
* Copyright 2023 by XGBoost contributors
*/
#include <array> // std::array
#include <cstddef> // std::size_t
#include <cstdint> // std::int32_t
#include <vector> // std::vector
@@ -170,10 +171,9 @@ class QuantileRegression : public ObjFunction {
common::Mean(ctx_, *base_score, &temp);
double meanq = temp(0) * sw;
if (info.IsRowSplit()) {
collective::Allreduce<collective::Operation::kSum>(&meanq, 1);
collective::Allreduce<collective::Operation::kSum>(&sw, 1);
}
std::array<double, 2> dat{meanq, sw};
collective::GlobalSum(info, &dat);
std::tie(meanq, sw) = std::tuple_cat(dat);
meanq /= (sw + kRtEps);
base_score->Reshape(1);
base_score->Data()->Fill(meanq);

6
src/objective/regression_obj.cu
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@@ -728,10 +728,8 @@ class MeanAbsoluteError : public ObjFunction {
std::transform(linalg::cbegin(out), linalg::cend(out), linalg::begin(out),
[w](float v) { return v * w; });
if (info.IsRowSplit()) {
collective::Allreduce<collective::Operation::kSum>(out.Values().data(), out.Values().size());
collective::Allreduce<collective::Operation::kSum>(&w, 1);
}
collective::GlobalSum(info, &out.Values());
collective::GlobalSum(info, &w, 1);
if (common::CloseTo(w, 0.0)) {
// Mostly for handling empty dataset test.