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Multi-GPU support in GPUPredictor. #3738

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merged 8 commits into from
Oct 24, 2018
Merged

Multi-GPU support in GPUPredictor. #3738

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9f50ad7
Multi-GPU support in GPUPredictor.
canonizer Sep 28, 2018
47d764f
Merge branch 'master' into mgpu-predictor-2
canonizer Oct 21, 2018
801f671
Replaced pointers with spans in GPUPredictor.
canonizer Oct 21, 2018
55980e4
Added a multi-GPU predictor test.
canonizer Oct 21, 2018
10bc710
Fix multi-gpu test.
trivialfis Oct 23, 2018
6a31dc2
Fix n_rows < n_gpus.
trivialfis Oct 23, 2018
01a35b6
Remove commented code.
trivialfis Oct 24, 2018
96fe214
Remove commented code.
trivialfis Oct 24, 2018
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2 changes: 1 addition & 1 deletion src/common/span.h
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Expand Up @@ -120,7 +120,7 @@ class SpanIterator {

using reference = typename std::conditional< // NOLINT
IsConst, const ElementType, ElementType>::type&;
using pointer = typename std::add_pointer<reference>::type&; // NOLINT
using pointer = typename std::add_pointer<reference>::type; // NOLINT

XGBOOST_DEVICE constexpr SpanIterator() : span_{nullptr}, index_{0} {}

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5 changes: 3 additions & 2 deletions src/gbm/gbtree.cc
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Expand Up @@ -194,8 +194,9 @@ class GBTree : public GradientBooster {
CHECK_EQ(in_gpair->Size() % ngroup, 0U)
<< "must have exactly ngroup*nrow gpairs";
// TODO(canonizer): perform this on GPU if HostDeviceVector has device set.
HostDeviceVector<GradientPair> tmp(in_gpair->Size() / ngroup,
GradientPair(), in_gpair->Distribution());
HostDeviceVector<GradientPair> tmp
(in_gpair->Size() / ngroup, GradientPair(),
GPUDistribution::Block(in_gpair->Distribution().Devices()));
const auto& gpair_h = in_gpair->ConstHostVector();
auto nsize = static_cast<bst_omp_uint>(tmp.Size());
for (int gid = 0; gid < ngroup; ++gid) {
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2 changes: 1 addition & 1 deletion src/objective/hinge.cu
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Expand Up @@ -22,7 +22,7 @@ struct HingeObjParam : public dmlc::Parameter<HingeObjParam> {
int n_gpus;
int gpu_id;
DMLC_DECLARE_PARAMETER(HingeObjParam) {
DMLC_DECLARE_FIELD(n_gpus).set_default(0).set_lower_bound(0)
DMLC_DECLARE_FIELD(n_gpus).set_default(1).set_lower_bound(-1)
.describe("Number of GPUs to use for multi-gpu algorithms.");
DMLC_DECLARE_FIELD(gpu_id)
.set_lower_bound(0)
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14 changes: 1 addition & 13 deletions src/objective/multiclass_obj.cu
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Expand Up @@ -31,7 +31,7 @@ struct SoftmaxMultiClassParam : public dmlc::Parameter<SoftmaxMultiClassParam> {
DMLC_DECLARE_PARAMETER(SoftmaxMultiClassParam) {
DMLC_DECLARE_FIELD(num_class).set_lower_bound(1)
.describe("Number of output class in the multi-class classification.");
DMLC_DECLARE_FIELD(n_gpus).set_default(-1).set_lower_bound(-1)
DMLC_DECLARE_FIELD(n_gpus).set_default(1).set_lower_bound(-1)
.describe("Number of GPUs to use for multi-gpu algorithms.");
DMLC_DECLARE_FIELD(gpu_id)
.set_lower_bound(0)
Expand Down Expand Up @@ -64,10 +64,6 @@ class SoftmaxMultiClassObj : public ObjFunction {
const int nclass = param_.num_class;
const auto ndata = static_cast<int64_t>(preds.Size() / nclass);

// clear out device memory;
out_gpair->Reshard(GPUSet::Empty());
preds.Reshard(GPUSet::Empty());

out_gpair->Reshard(GPUDistribution::Granular(devices_, nclass));
info.labels_.Reshard(GPUDistribution::Block(devices_));
info.weights_.Reshard(GPUDistribution::Block(devices_));
Expand Down Expand Up @@ -109,11 +105,6 @@ class SoftmaxMultiClassObj : public ObjFunction {
}, common::Range{0, ndata}, devices_, false)
.Eval(out_gpair, &info.labels_, &preds, &info.weights_, &label_correct_);

out_gpair->Reshard(GPUSet::Empty());
out_gpair->Reshard(GPUDistribution::Block(devices_));
preds.Reshard(GPUSet::Empty());
preds.Reshard(GPUDistribution::Block(devices_));

std::vector<int>& label_correct_h = label_correct_.HostVector();
for (auto const flag : label_correct_h) {
if (flag != 1) {
Expand All @@ -136,7 +127,6 @@ class SoftmaxMultiClassObj : public ObjFunction {
const auto ndata = static_cast<int64_t>(io_preds->Size() / nclass);
max_preds_.Resize(ndata);

io_preds->Reshard(GPUSet::Empty()); // clear out device memory
if (prob) {
common::Transform<>::Init(
[=] XGBOOST_DEVICE(size_t _idx, common::Span<bst_float> _preds) {
Expand Down Expand Up @@ -166,8 +156,6 @@ class SoftmaxMultiClassObj : public ObjFunction {
io_preds->Resize(max_preds_.Size());
io_preds->Copy(max_preds_);
}
io_preds->Reshard(GPUSet::Empty()); // clear out device memory
io_preds->Reshard(GPUDistribution::Block(devices_));
}

private:
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2 changes: 1 addition & 1 deletion src/objective/regression_obj.cu
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Expand Up @@ -34,7 +34,7 @@ struct RegLossParam : public dmlc::Parameter<RegLossParam> {
DMLC_DECLARE_PARAMETER(RegLossParam) {
DMLC_DECLARE_FIELD(scale_pos_weight).set_default(1.0f).set_lower_bound(0.0f)
.describe("Scale the weight of positive examples by this factor");
DMLC_DECLARE_FIELD(n_gpus).set_default(-1).set_lower_bound(-1)
DMLC_DECLARE_FIELD(n_gpus).set_default(1).set_lower_bound(-1)
.describe("Number of GPUs to use for multi-gpu algorithms.");
DMLC_DECLARE_FIELD(gpu_id)
.set_lower_bound(0)
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