Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Multi-GPU support in GPUPredictor. #3738

Merged
merged 8 commits into from
Oct 24, 2018
Merged

Multi-GPU support in GPUPredictor. #3738

Show file tree
Hide file tree
Changes from 4 commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
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
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion src/common/span.h
View file
Open in desktop
Original file line number Diff line number Diff line change
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} {}

Expand Down
5 changes: 3 additions & 2 deletions src/gbm/gbtree.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
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) {
Expand Down
2 changes: 1 addition & 1 deletion src/objective/hinge.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
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)
Expand Down
15 changes: 4 additions & 11 deletions src/objective/multiclass_obj.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
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 @@ -65,8 +65,8 @@ class SoftmaxMultiClassObj : public ObjFunction {
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(GPUSet::Empty());
// preds.Reshard(GPUSet::Empty());
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Why are we commenting out lines? If they are not needed, we should just remove them

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Done.


out_gpair->Reshard(GPUDistribution::Granular(devices_, nclass));
info.labels_.Reshard(GPUDistribution::Block(devices_));
Expand Down Expand Up @@ -109,11 +109,6 @@ 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 +131,7 @@ 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
// 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 +161,6 @@ 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:
Expand Down
2 changes: 1 addition & 1 deletion src/objective/regression_obj.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
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)
Expand Down
Loading