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Author SHA1 Message Date
Will Pazner 552d6857cb Add GPU scan support for Array<T>::PartialSum 2025-10-21 09:57:37 -07:00
Will Pazner a37d46e917 Fix comments in scan.hpp 2025-10-21 09:57:37 -07:00
Will Pazner 4acdb072b6 Add more device support to Array<T> 2025-10-21 09:57:37 -07:00
Will Pazner 9dbb184537 Remove need to explicitly pass workspace array to reducers 2025-10-21 09:57:37 -07:00
Will Pazner d67762a1c9 Move contents of array.cpp to array.hpp
Remove explicit template instantiations
2025-10-20 15:38:54 -07:00
6 changed files with 314 additions and 303 deletions
-214
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@@ -1,214 +0,0 @@
// Copyright (c) 2010-2025, Lawrence Livermore National Security, LLC. Produced
// at the Lawrence Livermore National Laboratory. All Rights reserved. See files
// LICENSE and NOTICE for details. LLNL-CODE-806117.
//
// This file is part of the MFEM library. For more information and source code
// availability visit https://mfem.org.
//
// MFEM is free software; you can redistribute it and/or modify it under the
// terms of the BSD-3 license. We welcome feedback and contributions, see file
// CONTRIBUTING.md for details.
// Abstract array data type
#include "array.hpp"
#include "../general/forall.hpp"
#include <fstream>
#include <type_traits>
namespace mfem
{
template <class T>
void Array<T>::Print(std::ostream &os, int width) const
{
for (int i = 0; i < size; i++)
{
os << data[i];
if ( !((i+1) % width) || i+1 == size )
{
os << '\n';
}
else
{
os << " ";
}
}
}
template <class T>
void Array<T>::Save(std::ostream &os, int fmt) const
{
if (fmt == 0)
{
os << size << '\n';
}
for (int i = 0; i < size; i++)
{
os << operator[](i) << '\n';
}
}
template <class T>
void Array<T>::Load(std::istream &in, int fmt)
{
if (fmt == 0)
{
int new_size;
in >> new_size;
SetSize(new_size);
}
for (int i = 0; i < size; i++)
{
in >> operator[](i);
}
}
template <class T>
T Array<T>::Max() const
{
MFEM_ASSERT(size > 0, "Array is empty with size " << size);
T max = operator[](0);
for (int i = 1; i < size; i++)
{
if (max < operator[](i))
{
max = operator[](i);
}
}
return max;
}
template <class T>
T Array<T>::Min() const
{
MFEM_ASSERT(size > 0, "Array is empty with size " << size);
T min = operator[](0);
for (int i = 1; i < size; i++)
{
if (operator[](i) < min)
{
min = operator[](i);
}
}
return min;
}
// Partial Sum
template <class T>
void Array<T>::PartialSum()
{
T sum = static_cast<T>(0);
for (int i = 0; i < size; i++)
{
sum+=operator[](i);
operator[](i) = sum;
}
}
template <class T>
void Array<T>::Abs()
{
static_assert(std::is_arithmetic<T>::value, "Use with arithmetic types!");
const bool useDevice = UseDevice();
const int N = size;
auto y = ReadWrite(useDevice);
mfem::forall_switch(useDevice, N, [=] MFEM_HOST_DEVICE (int i)
{
y[i] = std::abs(y[i]);
});
}
// Sum
template <class T>
T Array<T>::Sum() const
{
T sum = static_cast<T>(0);
for (int i = 0; i < size; i++)
{
sum+=operator[](i);
}
return sum;
}
template <class T>
int Array<T>::IsSorted() const
{
T val_prev = operator[](0), val;
for (int i = 1; i < size; i++)
{
val=operator[](i);
if (val < val_prev)
{
return 0;
}
val_prev = val;
}
return 1;
}
template <class T>
bool Array<T>::IsConstant() const
{
if (size < 2) { return true; }
const T v0 = data[0];
for (int i = 1; i < size; i++)
{
if (data[i] != v0)
{
return false;
}
}
return true;
}
template <class T>
void Array2D<T>::Load(const char *filename, int fmt)
{
std::ifstream in;
in.open(filename, std::ifstream::in);
MFEM_VERIFY(in.is_open(), "File " << filename << " does not exist.");
Load(in, fmt);
in.close();
}
template <class T>
void Array2D<T>::Print(std::ostream &os, int width_)
{
int height = this->NumRows();
int width = this->NumCols();
for (int i = 0; i < height; i++)
{
os << "[row " << i << "]\n";
for (int j = 0; j < width; j++)
{
os << (*this)(i,j);
if ( (j+1) == width_ || (j+1) % width_ == 0 )
{
os << '\n';
}
else
{
os << ' ';
}
}
}
}
template class Array<char>;
template class Array<int>;
template class Array<long long>;
template class Array<real_t>;
template class Array2D<int>;
template class Array2D<real_t>;
} // namespace mfem
+213 -15
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@@ -16,9 +16,13 @@
#include "mem_manager.hpp"
#include "device.hpp"
#include "error.hpp"
#include "forall.hpp"
#include "globals.hpp"
#include "reducers.hpp"
#include "scan.hpp"
#include <iostream>
#include <fstream>
#include <cstdlib>
#include <cstring>
#include <algorithm>
@@ -135,6 +139,8 @@ public:
/// Return the device flag of the Memory object used by the Array
bool UseDevice() const { return data.UseDevice(); }
void UseDevice(bool use_dev) { data.UseDevice(use_dev); }
/// Return true if the data will be deleted by the Array
inline bool OwnsData() const { return data.OwnsHostPtr(); }
@@ -275,11 +281,11 @@ public:
/** @brief Find the maximal element in the array, using the comparison
operator `<` for class T. */
T Max() const;
inline T Max() const;
/** @brief Find the minimal element in the array, using the comparison
operator `<` for class T. */
T Min() const;
inline T Min() const;
/// Sorts the array in ascending order. This requires operator< to be defined for T.
void Sort() { std::sort((T*)data, data + size); }
@@ -297,22 +303,22 @@ public:
}
/// Return 1 if the array is sorted from lowest to highest. Otherwise return 0.
int IsSorted() const;
inline int IsSorted() const;
/// Does the Array have Size zero.
bool IsEmpty() const { return Size() == 0; }
/// Return true if all entries of the array are the same.
bool IsConstant() const;
inline bool IsConstant() const;
/// Fill the entries of the array with the cumulative sum of the entries.
void PartialSum();
inline void PartialSum();
/// Replace each entry of the array with its absolute value.
void Abs();
inline void Abs();
/// Return the sum of all the array entries using the '+'' operator for class 'T'.
T Sum() const;
inline T Sum() const;
/// Set all entries of the array to the provided constant.
inline void operator=(const T &a);
@@ -797,8 +803,14 @@ template <typename T> template <typename CT>
inline Array<T> &Array<T>::operator=(const Array<CT> &src)
{
SetSize(src.Size());
for (int i = 0; i < size; i++) { (*this)[i] = T(src[i]); }
return *this;
const bool use_dev = UseDevice() || src.UseDevice();
const auto x = src.Read(use_dev);
auto y = Write(use_dev);
mfem::forall_switch(use_dev, size, [=] MFEM_HOST_DEVICE (int i)
{
y[i] = x[i];
});
}
template <class T>
@@ -1014,19 +1026,24 @@ template <class T>
inline void Array<T>::GetSubArray(int offset, int sa_size, Array<T> &sa) const
{
sa.SetSize(sa_size);
for (int i = 0; i < sa_size; i++)
const bool use_dev = UseDevice() || sa.UseDevice();
const auto x = Read(use_dev);
auto y = sa.Write(use_dev);
mfem::forall_switch(use_dev, sa_size, [=] MFEM_HOST_DEVICE (int i)
{
sa[i] = (*this)[offset+i];
}
y[i] = x[offset + i];
});
}
template <class T>
inline void Array<T>::operator=(const T &a)
{
for (int i = 0; i < size; i++)
const bool use_dev = UseDevice();
auto x = Write(use_dev);
mfem::forall_switch(use_dev, size, [=] MFEM_HOST_DEVICE (int i)
{
data[i] = a;
}
x[i] = a;
});
}
template <class T>
@@ -1035,6 +1052,153 @@ inline void Array<T>::Assign(const T *p)
data.CopyFromHost(p, Size());
}
template <class T>
inline void Array<T>::Print(std::ostream &os, int width) const
{
for (int i = 0; i < size; i++)
{
os << data[i];
if ( !((i+1) % width) || i+1 == size )
{
os << '\n';
}
else
{
os << " ";
}
}
}
template <class T>
inline void Array<T>::Save(std::ostream &os, int fmt) const
{
if (fmt == 0)
{
os << size << '\n';
}
for (int i = 0; i < size; i++)
{
os << operator[](i) << '\n';
}
}
template <class T>
void Array<T>::Load(std::istream &in, int fmt)
{
if (fmt == 0)
{
int new_size;
in >> new_size;
SetSize(new_size);
}
for (int i = 0; i < size; i++)
{
in >> operator[](i);
}
}
template <class T>
inline T Array<T>::Max() const
{
MFEM_ASSERT(size > 0, "Array is empty with size " << size);
T max = operator[](0);
for (int i = 1; i < size; i++)
{
if (max < operator[](i))
{
max = operator[](i);
}
}
return max;
}
template <class T>
inline T Array<T>::Min() const
{
MFEM_ASSERT(size > 0, "Array is empty with size " << size);
T min = operator[](0);
for (int i = 1; i < size; i++)
{
if (operator[](i) < min)
{
min = operator[](i);
}
}
return min;
}
// Partial Sum
template <class T>
inline void Array<T>::PartialSum()
{
auto data_ptr = ReadWrite(UseDevice());
InclusiveScan(UseDevice(), data_ptr, data_ptr, size);
}
template <class T>
inline void Array<T>::Abs()
{
static_assert(std::is_arithmetic<T>::value, "Use with arithmetic types!");
const bool useDevice = UseDevice();
const int N = size;
auto y = ReadWrite(useDevice);
mfem::forall_switch(useDevice, N, [=] MFEM_HOST_DEVICE (int i)
{
y[i] = std::abs(y[i]);
});
}
// Sum
template <class T>
inline T Array<T>::Sum() const
{
T sum = static_cast<T>(0);
if (size > 0)
{
const auto m_data = Read(UseDevice());
reduce(size, sum, [=] MFEM_HOST_DEVICE(int i, T &r) { r += m_data[i]; },
/* */ SumReducer<T> {}, UseDevice());
}
return sum;
}
template <class T>
inline int Array<T>::IsSorted() const
{
T val_prev = operator[](0), val;
for (int i = 1; i < size; i++)
{
val=operator[](i);
if (val < val_prev)
{
return 0;
}
val_prev = val;
}
return 1;
}
template <class T>
inline bool Array<T>::IsConstant() const
{
if (size < 2) { return true; }
const T v0 = data[0];
for (int i = 1; i < size; i++)
{
if (data[i] != v0)
{
return false;
}
}
return true;
}
template <class T>
inline const T &Array2D<T>::operator()(int i, int j) const
@@ -1074,6 +1238,40 @@ inline T *Array2D<T>::operator[](int i)
return &array1d[i*N];
}
template <class T>
void Array2D<T>::Load(const char *filename, int fmt)
{
std::ifstream in;
in.open(filename, std::ifstream::in);
MFEM_VERIFY(in.is_open(), "File " << filename << " does not exist.");
Load(in, fmt);
in.close();
}
template <class T>
void Array2D<T>::Print(std::ostream &os, int width_)
{
int height = this->NumRows();
int width = this->NumCols();
for (int i = 0; i < height; i++)
{
os << "[row " << i << "]\n";
for (int j = 0; j < width; j++)
{
os << (*this)(i,j);
if ( (j+1) == width_ || (j+1) % width_ == 0 )
{
os << '\n';
}
else
{
os << ' ';
}
}
}
}
template <class T>
inline void Swap(Array2D<T> &a, Array2D<T> &b)
+29 -10
View File
@@ -12,7 +12,6 @@
#ifndef MFEM_REDUCERS_HPP
#define MFEM_REDUCERS_HPP
#include "array.hpp"
#include "forall.hpp"
#include <cmath>
@@ -514,6 +513,33 @@ template<class B, class R> struct reduction_kernel
}
}
};
template <class T>
class ReductionWorkspace
{
Memory<T> workspace;
static ReductionWorkspace &Instance()
{
static ReductionWorkspace instance;
return instance;
}
~ReductionWorkspace() { workspace.Delete(); }
public:
static T *Get(int num_blocks)
{
ReductionWorkspace &instance = Instance();
if (instance.workspace.Capacity() < num_blocks)
{
instance.workspace.Delete();
instance.workspace.New(num_blocks, MemoryType::HOST_PINNED);
}
return instance.workspace;
}
};
}
/**
@@ -529,8 +555,7 @@ template<class B, class R> struct reduction_kernel
@tparam T value_type to operate on
*/
template <class T, class B, class R>
void reduce(int N, T &res, B &&body, const R &reducer, bool use_dev,
Array<T> &workspace)
void reduce(int N, T &res, B &&body, const R &reducer, bool use_dev)
{
if (N == 0)
{
@@ -567,13 +592,7 @@ void reduce(int N, T &res, B &&body, const R &reducer, bool use_dev,
red_type red{nullptr, std::forward<B>(body), reducer, N, items_per_thread};
// allocate res to fit block_size entries
auto mt = workspace.GetMemory().GetMemoryType();
if (mt != MemoryType::HOST_PINNED && mt != MemoryType::MANAGED)
{
mt = MemoryType::HOST_PINNED;
}
workspace.SetSize(nblocks, mt);
auto work = workspace.HostWrite();
auto work = internal::ReductionWorkspace<T>::Get(nblocks);
red.work = work;
forall_2D(nblocks, block_size, 1, std::move(red));
// wait for results
+52 -22
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@@ -28,8 +28,37 @@
namespace mfem
{
/// Equivalent to InclusiveScan(use_dev, d_in, d_out, num_items, workspace,
/// std::plus<>{})
namespace internal
{
class ScanWorkspace
{
Memory<std::byte> workspace;
static ScanWorkspace &Instance()
{
static ScanWorkspace instance;
return instance;
}
~ScanWorkspace() { workspace.Delete(); }
public:
static std::byte *Get(int num_bytes)
{
ScanWorkspace &instance = Instance();
if (Size() < num_bytes)
{
instance.workspace.Delete();
instance.workspace.New(num_bytes);
}
return instance.workspace.Write(MemoryClass::DEVICE, Size());
}
static int Size()
{
return Instance().workspace.Capacity();
}
};
}
/// Equivalent to InclusiveScan(use_dev, d_in, d_out, num_items, std::plus<>{})
template <class InputIt, class OutputIt>
void InclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items)
{
@@ -37,12 +66,12 @@ void InclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items)
#if defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP)
if (use_dev && mfem::Device::Allows(Backend::CUDA_MASK | Backend::HIP_MASK))
{
static Array<std::byte> workspace;
size_t bytes = workspace.Size();
if (bytes)
using internal::ScanWorkspace;
size_t bytes = ScanWorkspace::Size();
if (bytes > 0)
{
auto err = MFEM_CUB_NAMESPACE::DeviceScan::InclusiveSum(
workspace.Write(), bytes, d_in, d_out, num_items);
ScanWorkspace::Get(bytes), bytes, d_in, d_out, num_items);
#if defined(MFEM_USE_CUDA)
if (err == cudaSuccess)
{
@@ -57,11 +86,12 @@ void InclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items)
}
// try allocating a larger buffer
bytes = 0;
// get size of buffer
MFEM_GPU_CHECK(MFEM_CUB_NAMESPACE::DeviceScan::InclusiveSum(
nullptr, bytes, d_in, d_out, num_items));
workspace.SetSize(bytes);
// resize buffer (in ScanWorkspace::Get) and try again
MFEM_GPU_CHECK(MFEM_CUB_NAMESPACE::DeviceScan::InclusiveSum(
workspace.Write(), bytes, d_in, d_out, num_items));
ScanWorkspace::Get(bytes), bytes, d_in, d_out, num_items));
return;
}
#endif
@@ -101,12 +131,13 @@ void InclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items,
#if defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP)
if (use_dev && mfem::Device::Allows(Backend::CUDA_MASK | Backend::HIP_MASK))
{
static Array<std::byte> workspace;
size_t bytes = workspace.Size();
if (bytes)
using internal::ScanWorkspace;
size_t bytes = ScanWorkspace::Size();
if (bytes > 0)
{
auto err = MFEM_CUB_NAMESPACE::DeviceScan::InclusiveScan(
workspace.Write(), bytes, d_in, d_out, scan_op, num_items);
ScanWorkspace::Get(bytes), bytes, d_in, d_out, scan_op,
num_items);
#if defined(MFEM_USE_CUDA)
if (err == cudaSuccess)
{
@@ -123,9 +154,9 @@ void InclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items,
bytes = 0;
MFEM_GPU_CHECK(MFEM_CUB_NAMESPACE::DeviceScan::InclusiveScan(
nullptr, bytes, d_in, d_out, scan_op, num_items));
workspace.SetSize(bytes);
MFEM_GPU_CHECK(MFEM_CUB_NAMESPACE::DeviceScan::InclusiveScan(
workspace.Write(), bytes, d_in, d_out, scan_op, num_items));
ScanWorkspace::Get(bytes), bytes, d_in, d_out, scan_op,
num_items));
return;
}
#endif
@@ -164,13 +195,13 @@ void ExclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items,
#if defined(MFEM_USE_CUDA) || defined(MFEM_USE_HIP)
if (use_dev && mfem::Device::Allows(Backend::CUDA_MASK | Backend::HIP_MASK))
{
static Array<std::byte> workspace;
size_t bytes = workspace.Size();
using internal::ScanWorkspace;
size_t bytes = ScanWorkspace::Size();
if (bytes)
{
auto err = MFEM_CUB_NAMESPACE::DeviceScan::ExclusiveScan(
workspace.Write(), bytes, d_in, d_out, scan_op, init_value,
num_items);
ScanWorkspace::Get(bytes), bytes, d_in, d_out, scan_op,
init_value, num_items);
#if defined(MFEM_USE_CUDA)
if (err == cudaSuccess)
{
@@ -187,10 +218,9 @@ void ExclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items,
bytes = 0;
MFEM_GPU_CHECK(MFEM_CUB_NAMESPACE::DeviceScan::ExclusiveScan(
nullptr, bytes, d_in, d_out, scan_op, init_value, num_items));
workspace.SetSize(bytes);
MFEM_GPU_CHECK(MFEM_CUB_NAMESPACE::DeviceScan::ExclusiveScan(
workspace.Write(), bytes, d_in, d_out, scan_op, init_value,
num_items));
ScanWorkspace::Get(bytes), bytes, d_in, d_out, scan_op,
init_value, num_items));
return;
}
#endif
@@ -213,7 +243,7 @@ void ExclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items,
}
/// Equivalent to ExclusiveScan(use_dev, d_in, d_out, num_items, init_value,
/// workspace, std::plus<>{})
/// std::plus<>{})
template <class InputIt, class OutputIt, class T>
void ExclusiveScan(bool use_dev, InputIt d_in, OutputIt d_out, size_t num_items,
T init_value)
+8 -20
View File
@@ -92,18 +92,6 @@ struct LpReducer
}
};
static Array<real_t>& vector_workspace()
{
static Array<real_t> instance;
return instance;
}
static Array<DevicePair<real_t, real_t>> &Lpvector_workspace()
{
static Array<DevicePair<real_t, real_t>> instance;
return instance;
}
Vector::Vector(const Vector &v)
{
const int s = v.Size();
@@ -991,7 +979,7 @@ real_t Vector::Norml2() const
}
}
},
L2Reducer{}, UseDevice(), Lpvector_workspace());
L2Reducer{}, UseDevice());
// final answer
return res.second * sqrt(res.first);
}
@@ -1006,7 +994,7 @@ real_t Vector::Normlinf() const
{
r = fmax(r, fabs(m_data[i]));
},
MaxReducer<real_t> {}, UseDevice(), vector_workspace());
MaxReducer<real_t> {}, UseDevice());
return res;
}
@@ -1020,7 +1008,7 @@ real_t Vector::Norml1() const
{
r += fabs(m_data[i]);
},
SumReducer<real_t> {}, UseDevice(), vector_workspace());
SumReducer<real_t> {}, UseDevice());
return res;
}
@@ -1063,7 +1051,7 @@ real_t Vector::Normlp(real_t p) const
}
}
},
LpReducer{p}, UseDevice(), Lpvector_workspace());
LpReducer{p}, UseDevice());
// final answer
return res.second * pow(res.first, 1.0 / p);
} // end if p < infinity()
@@ -1096,7 +1084,7 @@ real_t Vector::operator*(const Vector &v) const
{
r += m_data[i] * v_data[i];
},
SumReducer<real_t> {}, use_dev, vector_workspace());
SumReducer<real_t> {}, use_dev);
return res;
};
@@ -1167,7 +1155,7 @@ real_t Vector::Min() const
{
r = fmin(r, m_data[i]);
},
MinReducer<real_t> {}, use_dev, vector_workspace());
MinReducer<real_t> {}, use_dev);
return res;
};
@@ -1213,7 +1201,7 @@ real_t Vector::Max() const
{
r = fmax(r, m_data[i]);
},
MaxReducer<real_t> {}, use_dev, vector_workspace());
MaxReducer<real_t> {}, use_dev);
return res;
};
@@ -1248,7 +1236,7 @@ real_t Vector::Sum() const
{
r += m_data[i];
},
SumReducer<real_t> {}, UseDevice(), vector_workspace());
SumReducer<real_t> {}, UseDevice());
return res;
}
+12 -22
View File
@@ -22,7 +22,6 @@ using namespace mfem;
TEST_CASE("Reduce Sum", "[Reduction],[GPU]")
{
Array<int> workspace;
Array<int> a(1000);
a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -36,7 +35,7 @@ TEST_CASE("Reduce Sum", "[Reduction],[GPU]")
int res = 0;
mfem::reduce(
a.Size(), res, [=] MFEM_HOST_DEVICE(int i, int &r) { r += dptr[i]; },
SumReducer<int> {}, use_dev, workspace);
SumReducer<int> {}, use_dev);
// correct for even-length summations
int expected = (AsConst(a)[0] + AsConst(a)[a.Size() - 1]) * a.Size() / 2;
CAPTURE(use_dev);
@@ -46,7 +45,6 @@ TEST_CASE("Reduce Sum", "[Reduction],[GPU]")
TEST_CASE("Reduce Mult", "[Reduction],[GPU]")
{
Array<long long> workspace;
Array<long long> a(64);
a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -64,7 +62,7 @@ TEST_CASE("Reduce Mult", "[Reduction],[GPU]")
mfem::reduce(
a.Size(), res,
[=] MFEM_HOST_DEVICE(int i, long long &r) { r *= dptr[i]; },
MultReducer<long long> {}, use_dev, workspace);
MultReducer<long long> {}, use_dev);
long long expected = 0;
CAPTURE(use_dev);
REQUIRE(res == expected);
@@ -76,7 +74,7 @@ TEST_CASE("Reduce Mult", "[Reduction],[GPU]")
mfem::reduce(
a.Size(), res,
[=] MFEM_HOST_DEVICE(int i, long long &r) { r *= dptr[i]; },
MultReducer<long long> {}, use_dev, workspace);
MultReducer<long long> {}, use_dev);
long long expected = 21936950640377856;
CAPTURE(use_dev);
REQUIRE(res == expected);
@@ -86,7 +84,6 @@ TEST_CASE("Reduce Mult", "[Reduction],[GPU]")
TEST_CASE("Reduce BAnd", "[Reduction],[GPU]")
{
Array<unsigned> workspace;
Array<unsigned> a(10);
SECTION("{ Bit unset }")
{
@@ -108,7 +105,7 @@ TEST_CASE("Reduce BAnd", "[Reduction],[GPU]")
mfem::reduce(
a.Size(), res,
[=] MFEM_HOST_DEVICE(int i, unsigned &r) { r &= dptr[i]; },
BAndReducer<unsigned> {}, use_dev, workspace);
BAndReducer<unsigned> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res == ((~1u) & ~(1u << unset_bit)));
REQUIRE((res & (1u << unset_bit)) == 0);
@@ -132,7 +129,7 @@ TEST_CASE("Reduce BAnd", "[Reduction],[GPU]")
mfem::reduce(
a.Size(), res,
[=] MFEM_HOST_DEVICE(int i, unsigned &r) { r &= dptr[i]; },
BAndReducer<unsigned> {}, use_dev, workspace);
BAndReducer<unsigned> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res == (1u << set_bit));
}
@@ -141,7 +138,6 @@ TEST_CASE("Reduce BAnd", "[Reduction],[GPU]")
TEST_CASE("Reduce BOr", "[Reduction],[GPU]")
{
Array<unsigned> workspace;
Array<unsigned> a(0x210);
a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -157,7 +153,7 @@ TEST_CASE("Reduce BOr", "[Reduction],[GPU]")
mfem::reduce(
a.Size(), res,
[=] MFEM_HOST_DEVICE(int i, unsigned &r) { r |= dptr[i]; },
BOrReducer<unsigned> {}, use_dev, workspace);
BOrReducer<unsigned> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res == 0x3ffu);
}
@@ -165,7 +161,6 @@ TEST_CASE("Reduce BOr", "[Reduction],[GPU]")
TEST_CASE("Reduce Min", "[Reduction],[GPU]")
{
Array<int> workspace;
Array<int> a(1000);
auto hptr = a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -190,7 +185,7 @@ TEST_CASE("Reduce Min", "[Reduction],[GPU]")
r = dptr[i];
}
},
MinReducer<int> {}, use_dev, workspace);
MinReducer<int> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res == -10);
}
@@ -198,7 +193,6 @@ TEST_CASE("Reduce Min", "[Reduction],[GPU]")
TEST_CASE("Reduce Max", "[Reduction],[GPU]")
{
Array<int> workspace;
Array<int> a(1000);
auto hptr = a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -223,7 +217,7 @@ TEST_CASE("Reduce Max", "[Reduction],[GPU]")
r = dptr[i];
}
},
MaxReducer<int> {}, use_dev, workspace);
MaxReducer<int> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res == 999 - 10);
}
@@ -231,7 +225,6 @@ TEST_CASE("Reduce Max", "[Reduction],[GPU]")
TEST_CASE("Reduce MinMax", "[Reduction],[GPU]")
{
Array<DevicePair<int, int>> workspace;
Array<int> a(1000);
auto hptr = a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -262,7 +255,7 @@ TEST_CASE("Reduce MinMax", "[Reduction],[GPU]")
r.second = dptr[i];
}
},
MinMaxReducer<int> {}, use_dev, workspace);
MinMaxReducer<int> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res.first == -10);
REQUIRE(res.second == a.Size() - 11);
@@ -271,7 +264,6 @@ TEST_CASE("Reduce MinMax", "[Reduction],[GPU]")
TEST_CASE("Reduce ArgMin", "[Reduction],[GPU]")
{
Array<DevicePair<double, int>> workspace;
Array<double> a(1000);
auto hptr = a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -297,7 +289,7 @@ TEST_CASE("Reduce ArgMin", "[Reduction],[GPU]")
r.second = i;
}
},
ArgMinReducer<double, int> {}, use_dev, workspace);
ArgMinReducer<double, int> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res.first == -10);
REQUIRE(res.second >= 0);
@@ -308,7 +300,6 @@ TEST_CASE("Reduce ArgMin", "[Reduction],[GPU]")
TEST_CASE("Reduce ArgMax", "[Reduction],[GPU]")
{
Array<DevicePair<double, int>> workspace;
Array<double> a(1000);
auto hptr = a.HostReadWrite();
@@ -337,7 +328,7 @@ TEST_CASE("Reduce ArgMax", "[Reduction],[GPU]")
r.second = i;
}
},
ArgMaxReducer<double, int> {}, use_dev, workspace);
ArgMaxReducer<double, int> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res.first == a.Size() - 11);
REQUIRE(res.second >= 0);
@@ -348,7 +339,6 @@ TEST_CASE("Reduce ArgMax", "[Reduction],[GPU]")
TEST_CASE("Reduce ArgMinMax", "[Reduction],[GPU]")
{
Array<MinMaxLocScalar<double, int>> workspace;
Array<double> a(1000);
auto hptr = a.HostReadWrite();
for (int i = 0; i < a.Size(); ++i)
@@ -383,7 +373,7 @@ TEST_CASE("Reduce ArgMinMax", "[Reduction],[GPU]")
r.max_loc = i;
}
},
ArgMinMaxReducer<double, int> {}, use_dev, workspace);
ArgMinMaxReducer<double, int> {}, use_dev);
CAPTURE(use_dev);
REQUIRE(res.min_val == -10);
REQUIRE(res.min_loc >= 0);