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Make HostDeviceVector single gpu only (#4773)

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* Make HostDeviceVector single gpu only
This commit is contained in:
Rong Ou
2019-08-25 14:51:13 -07:00
committed by Rory Mitchell
parent 41227d1933
commit 38ab79f889
54 changed files with 641 additions and 1621 deletions
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68
src/common/transform.h
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@@ -57,14 +57,10 @@ class Transform {
template <typename Functor>
struct Evaluator {
public:
Evaluator(Functor func, Range range, GPUSet devices, bool shard) :
Evaluator(Functor func, Range range, int device, bool shard) :
func_(func), range_{std::move(range)},
shard_{shard},
distribution_{GPUDistribution::Block(devices)} {}
Evaluator(Functor func, Range range, GPUDistribution dist,
bool shard) :
func_(func), range_{std::move(range)}, shard_{shard},
distribution_{std::move(dist)} {}
device_{device} {}
/*!
* \brief Evaluate the functor with input pointers to HostDeviceVector.
@@ -74,7 +70,7 @@ class Transform {
*/
template <typename... HDV>
void Eval(HDV... vectors) const {
bool on_device = !distribution_.IsEmpty();
bool on_device = device_ >= 0;
if (on_device) {
LaunchCUDA(func_, vectors...);
@@ -86,13 +82,13 @@ class Transform {
private:
// CUDA UnpackHDV
template <typename T>
Span<T> UnpackHDV(HostDeviceVector<T>* _vec, int _device) const {
auto span = _vec->DeviceSpan(_device);
Span<T> UnpackHDVOnDevice(HostDeviceVector<T>* _vec) const {
auto span = _vec->DeviceSpan();
return span;
}
template <typename T>
Span<T const> UnpackHDV(const HostDeviceVector<T>* _vec, int _device) const {
auto span = _vec->ConstDeviceSpan(_device);
Span<T const> UnpackHDVOnDevice(const HostDeviceVector<T>* _vec) const {
auto span = _vec->ConstDeviceSpan();
return span;
}
// CPU UnpackHDV
@@ -108,15 +104,15 @@ class Transform {
}
// Recursive unpack for Shard.
template <typename T>
void UnpackShard(GPUDistribution dist, const HostDeviceVector<T> *vector) const {
vector->Shard(dist);
void UnpackShard(int device, const HostDeviceVector<T> *vector) const {
vector->SetDevice(device);
}
template <typename Head, typename... Rest>
void UnpackShard(GPUDistribution dist,
void UnpackShard(int device,
const HostDeviceVector<Head> *_vector,
const HostDeviceVector<Rest> *... _vectors) const {
_vector->Shard(dist);
UnpackShard(dist, _vectors...);
_vector->SetDevice(device);
UnpackShard(device, _vectors...);
}
#if defined(__CUDACC__)
@@ -124,28 +120,20 @@ class Transform {
typename... HDV>
void LaunchCUDA(Functor _func, HDV*... _vectors) const {
if (shard_)
UnpackShard(distribution_, _vectors...);
UnpackShard(device_, _vectors...);
GPUSet devices = distribution_.Devices();
size_t range_size = *range_.end() - *range_.begin();
// Extract index to deal with possible old OpenMP.
size_t device_beg = *(devices.begin());
size_t device_end = *(devices.end());
#pragma omp parallel for schedule(static, 1) if (devices.Size() > 1)
for (omp_ulong device = device_beg; device < device_end; ++device) { // NOLINT
// Ignore other attributes of GPUDistribution for spliting index.
// This deals with situation like multi-class setting where
// granularity is used in data vector.
size_t shard_size = GPUDistribution::Block(devices).ShardSize(
range_size, devices.Index(device));
Range shard_range {0, static_cast<Range::DifferenceType>(shard_size)};
dh::safe_cuda(cudaSetDevice(device));
const int GRID_SIZE =
static_cast<int>(DivRoundUp(*(range_.end()), kBlockThreads));
detail::LaunchCUDAKernel<<<GRID_SIZE, kBlockThreads>>>(
_func, shard_range, UnpackHDV(_vectors, device)...);
}
// This deals with situation like multi-class setting where
// granularity is used in data vector.
size_t shard_size = range_size;
Range shard_range {0, static_cast<Range::DifferenceType>(shard_size)};
dh::safe_cuda(cudaSetDevice(device_));
const int GRID_SIZE =
static_cast<int>(DivRoundUp(*(range_.end()), kBlockThreads));
detail::LaunchCUDAKernel<<<GRID_SIZE, kBlockThreads>>>(
_func, shard_range, UnpackHDVOnDevice(_vectors)...);
}
#else
/*! \brief Dummy funtion defined when compiling for CPU. */
@@ -172,7 +160,7 @@ class Transform {
Range range_;
/*! \brief Whether sharding for vectors is required. */
bool shard_;
GPUDistribution distribution_;
int device_;
};
public:
@@ -191,15 +179,9 @@ class Transform {
*/
template <typename Functor>
static Evaluator<Functor> Init(Functor func, Range const range,
GPUSet const devices,
int device,
bool const shard = true) {
return Evaluator<Functor> {func, std::move(range), std::move(devices), shard};
}
template <typename Functor>
static Evaluator<Functor> Init(Functor func, Range const range,
GPUDistribution const dist,
bool const shard = true) {
return Evaluator<Functor> {func, std::move(range), std::move(dist), shard};
return Evaluator<Functor> {func, std::move(range), device, shard};
}
};