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Tidy sincos, memory, random, and soa headers #8

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0452e6b
Tidy sincos, memory, random, and soa headers
shsahiti Sep 17, 2026
9515b95
Fix namespace qualification and drop redundant xpu:: prefixes
shsahiti Sep 19, 2026
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68 changes: 34 additions & 34 deletions xpu/linear_algebra.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,7 @@ struct build_identity {
std::size_t stride;

DEVICE_ONLY
auto operator()(const xpu::array<std::size_t, 2uz>& index) const -> void {
auto operator()(const array<std::size_t, 2uz>& index) const -> void {
const auto row{index[0]};
const auto column{index[1]};

Expand All @@ -66,7 +66,7 @@ struct transpose_square {
std::size_t stride;

DEVICE_ONLY
auto operator()(const xpu::array<std::size_t, 2uz>& index) const -> void {
auto operator()(const array<std::size_t, 2uz>& index) const -> void {
const auto row{index[0]};
const auto column{index[1]};
const auto skip_pair{row >= column};
Expand All @@ -87,7 +87,7 @@ struct transpose_square {

inline auto create_cusolver_handle() -> cusolverDnHandle_t {
auto handle{cusolverDnHandle_t{}};
xpu::cu_check(cusolverDnCreate(&handle));
cu_check(cusolverDnCreate(&handle));
return handle;
}

Expand All @@ -103,14 +103,14 @@ inline auto getrf_workspace_size(
auto size{0};

if constexpr (std::same_as<T, float>) {
xpu::cu_check(cusolverDnSgetrf_bufferSize(
cu_check(cusolverDnSgetrf_bufferSize(
handle,
vendor_order, vendor_order,
nullptr, vendor_stride,
&size
));
} else {
xpu::cu_check(cusolverDnDgetrf_bufferSize(
cu_check(cusolverDnDgetrf_bufferSize(
handle,
vendor_order, vendor_order,
nullptr, vendor_stride,
Expand All @@ -135,14 +135,14 @@ inline auto potrf_workspace_size(
auto size{0};

if constexpr (std::same_as<T, float>) {
xpu::cu_check(cusolverDnSpotrf_bufferSize(
cu_check(cusolverDnSpotrf_bufferSize(
handle, CUBLAS_FILL_MODE_UPPER,
vendor_order,
nullptr, vendor_stride,
&size
));
} else {
xpu::cu_check(cusolverDnDpotrf_bufferSize(
cu_check(cusolverDnDpotrf_bufferSize(
handle, CUBLAS_FILL_MODE_UPPER,
vendor_order,
nullptr, vendor_stride,
Expand All @@ -169,14 +169,14 @@ inline auto cusolver_getrf(
const auto vendor_stride{xpu::detail::checked_cast<int>(stride)};

if constexpr (std::same_as<T, float>) {
xpu::cu_check(cusolverDnSgetrf(
cu_check(cusolverDnSgetrf(
handle,
vendor_order, vendor_order,
matrix, vendor_stride,
workspace, pivot, info
));
} else {
xpu::cu_check(cusolverDnDgetrf(
cu_check(cusolverDnDgetrf(
handle,
vendor_order, vendor_order,
matrix, vendor_stride,
Expand All @@ -200,15 +200,15 @@ inline auto cusolver_potrf(
const auto vendor_workspace_size{xpu::detail::checked_cast<int>(workspace_size)};

if constexpr (std::same_as<T, float>) {
xpu::cu_check(cusolverDnSpotrf(
cu_check(cusolverDnSpotrf(
handle, CUBLAS_FILL_MODE_UPPER,
vendor_order,
matrix, vendor_stride,
workspace, vendor_workspace_size,
info
));
} else {
xpu::cu_check(cusolverDnDpotrf(
cu_check(cusolverDnDpotrf(
handle, CUBLAS_FILL_MODE_UPPER,
vendor_order,
matrix, vendor_stride,
Expand Down Expand Up @@ -237,7 +237,7 @@ inline auto cusolver_getrs(
const auto vendor_solution_stride{xpu::detail::checked_cast<int>(solution_stride)};

if constexpr (std::same_as<T, float>) {
xpu::cu_check(cusolverDnSgetrs(
cu_check(cusolverDnSgetrs(
handle, operation,
vendor_order, vendor_right_hand_sides,
lower_upper, vendor_lower_upper_stride,
Expand All @@ -246,7 +246,7 @@ inline auto cusolver_getrs(
info
));
} else {
xpu::cu_check(cusolverDnDgetrs(
cu_check(cusolverDnDgetrs(
handle, operation,
vendor_order, vendor_right_hand_sides,
lower_upper, vendor_lower_upper_stride,
Expand Down Expand Up @@ -274,15 +274,15 @@ inline auto cusolver_potrs(
const auto vendor_solution_stride{xpu::detail::checked_cast<int>(solution_stride)};

if constexpr (std::same_as<T, float>) {
xpu::cu_check(cusolverDnSpotrs(
cu_check(cusolverDnSpotrs(
handle, CUBLAS_FILL_MODE_UPPER,
vendor_order, vendor_right_hand_sides,
factor, vendor_factor_stride,
solution, vendor_solution_stride,
info
));
} else {
xpu::cu_check(cusolverDnDpotrs(
cu_check(cusolverDnDpotrs(
handle, CUBLAS_FILL_MODE_UPPER,
vendor_order, vendor_right_hand_sides,
factor, vendor_factor_stride,
Expand Down Expand Up @@ -468,7 +468,7 @@ inline auto transpose_square(
stride
};

xpu::parallel_for(range, transpose);
parallel_for(range, transpose);
#else
for (auto row{0uz}; row < order; ++row) {
for (auto column{row + 1uz}; column < order; ++column) {
Expand Down Expand Up @@ -499,8 +499,8 @@ class cholesky_factorization {

#if defined(XPU_CUDA)
cusolverDnHandle_t handle_;
xpu::buffer<T> workspace_;
xpu::buffer<int> info_;
buffer<T> workspace_;
buffer<int> info_;
#endif

[[nodiscard]]
Expand Down Expand Up @@ -534,7 +534,7 @@ class cholesky_factorization {

~cholesky_factorization() {
#if defined(XPU_CUDA)
xpu::cu_check(cusolverDnDestroy(handle_));
cu_check(cusolverDnDestroy(handle_));
#endif
}

Expand All @@ -559,7 +559,7 @@ class cholesky_factorization {
);

auto info{0};
xpu::copy_n(&info, info_.data(), 1uz);
copy_n(&info, info_.data(), 1uz);
if (info < 0) {
detail::linalg_error("cuSOLVER potrf received an invalid argument");
}
Expand Down Expand Up @@ -595,7 +595,7 @@ class cholesky_factorization {
detail::linalg_error("rhs and solution must not alias");
}

xpu::copy_n(solution, rhs, order_);
copy_n(solution, rhs, order_);

#if defined(XPU_CUDA)
detail::cusolver_potrs(
Expand All @@ -606,7 +606,7 @@ class cholesky_factorization {
);

auto info{0};
xpu::copy_n(&info, info_.data(), 1uz);
copy_n(&info, info_.data(), 1uz);
if (info != 0) {
detail::linalg_error("cuSOLVER potrs received an invalid argument");
}
Expand Down Expand Up @@ -640,12 +640,12 @@ class lu_factorization {
#endif

#if defined(XPU_CUDA)
xpu::buffer<int> pivot_;
buffer<int> pivot_;
cusolverDnHandle_t handle_;
xpu::buffer<T> workspace_;
xpu::buffer<int> info_;
buffer<T> workspace_;
buffer<int> info_;
#else
xpu::buffer<lapack_int> pivot_;
buffer<lapack_int> pivot_;
#endif

[[nodiscard]]
Expand All @@ -661,7 +661,7 @@ class lu_factorization {

const auto matrix_size{xpu::detail::checked_mul(order, stride)};

static_cast<void>(xpu::detail::checked_bytes<T>(matrix_size));
static_cast<void>(bytes<T>(matrix_size));

return order;
}
Expand All @@ -682,7 +682,7 @@ class lu_factorization {

~lu_factorization() {
#if defined(XPU_CUDA)
xpu::cu_check(cusolverDnDestroy(handle_));
cu_check(cusolverDnDestroy(handle_));
#endif
}

Expand All @@ -707,7 +707,7 @@ class lu_factorization {
);

auto info{0};
xpu::copy_n(&info, info_.data(), 1uz);
copy_n(&info, info_.data(), 1uz);
if (info < 0) {
detail::linalg_error("cuSOLVER getrf received an invalid argument");
}
Expand Down Expand Up @@ -742,7 +742,7 @@ class lu_factorization {
detail::linalg_error("rhs and solution must not alias");
}

xpu::copy_n(solution, rhs, order_);
copy_n(solution, rhs, order_);

#if defined(XPU_CUDA)
detail::cusolver_getrs(
Expand All @@ -755,7 +755,7 @@ class lu_factorization {
);

auto info{0};
xpu::copy_n(&info, info_.data(), 1uz);
copy_n(&info, info_.data(), 1uz);
if (info != 0) {
detail::linalg_error("cuSOLVER getrs received an invalid argument");
}
Expand Down Expand Up @@ -797,7 +797,7 @@ class lu_factorization {
stride_
};

xpu::parallel_for(range, initialize);
parallel_for(range, initialize);

detail::cusolver_getrs(
handle_, CUBLAS_OP_N,
Expand All @@ -809,13 +809,13 @@ class lu_factorization {
);

auto info{0};
xpu::copy_n(&info, info_.data(), 1uz);
copy_n(&info, info_.data(), 1uz);
if (info != 0) {
detail::linalg_error("cuSOLVER getrs received an invalid argument");
}
#else
for (auto row{0uz}; row < order_; ++row) {
xpu::copy_n(
copy_n(
inverse + row * stride_,
lower_upper + row * stride_,
order_
Expand Down
13 changes: 7 additions & 6 deletions xpu/math.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -67,25 +67,26 @@ using xstd::ldexp; using xstd::frexp; using xstd::modf;

// Overflow safe version of (num + den - 1) / den
template <std::unsigned_integral T> [[nodiscard]] CUDA_CALLABLE
inline constexpr auto ceiling_div(T num, T den) noexcept -> T {
constexpr auto ceiling_div(T num, T den) noexcept -> T {
const auto zero_denominator{den == 0};

if (zero_denominator) {
xpu::detail::checked_error("zero ceiling division denominator");
}

const auto quotient{num / den + (num % den != 0)};
const auto quotient{ ( num / den ) + (num % den != 0)};

return quotient;
}


template <std::floating_point T> CUDA_CALLABLE
inline auto sincos(T arg, T* RESTRICT s, T* RESTRICT c) noexcept -> void {
inline auto sincos(T arg, T* RESTRICT sin, T* RESTRICT cos) noexcept -> void {
#if defined(__CUDA_ARCH__)
if constexpr (std::is_same_v<T, float>) { ::sincosf(arg, s, c); }
else { ::sincos(arg, s, c); }
if constexpr (std::is_same_v<T, float>) { ::sincosf(arg, sin, cos); }
else { ::sincos(arg, sin, cos); }
#else
*s = xpu::sin(arg); *c = xpu::cos(arg);
*sin = xpu::sin(arg); *cos = xpu::cos(arg);
#endif
}

Expand Down
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