// Copyright (c) 2017-2022, Lawrence Livermore National Security, LLC and other CEED contributors. // All Rights Reserved. See the top-level LICENSE and NOTICE files for details. // // SPDX-License-Identifier: BSD-2-Clause // // This file is part of CEED: http://github.com/ceed #include #include //------------------------------------------------------------------------------ // Kernel for set value on device //------------------------------------------------------------------------------ __global__ static void setValueK(CeedScalar *__restrict__ vec, CeedInt size, CeedScalar val) { int idx = threadIdx.x + blockDim.x * blockIdx.x; if (idx >= size) return; vec[idx] = val; } //------------------------------------------------------------------------------ // Set value on device memory //------------------------------------------------------------------------------ extern "C" int CeedDeviceSetValue_Hip(CeedScalar *d_array, CeedInt length, CeedScalar val) { const int bsize = 512; const int vecsize = length; int gridsize = vecsize / bsize; if (bsize * gridsize < vecsize) gridsize += 1; hipLaunchKernelGGL(setValueK, dim3(gridsize), dim3(bsize), 0, 0, d_array, length, val); return 0; } //------------------------------------------------------------------------------ // Kernel for taking reciprocal //------------------------------------------------------------------------------ __global__ static void rcpValueK(CeedScalar *__restrict__ vec, CeedInt size) { int idx = threadIdx.x + blockDim.x * blockIdx.x; if (idx >= size) return; if (fabs(vec[idx]) > 1E-16) vec[idx] = 1. / vec[idx]; } //------------------------------------------------------------------------------ // Take vector reciprocal in device memory //------------------------------------------------------------------------------ extern "C" int CeedDeviceReciprocal_Hip(CeedScalar *d_array, CeedInt length) { const int bsize = 512; const int vecsize = length; int gridsize = vecsize / bsize; if (bsize * gridsize < vecsize) gridsize += 1; hipLaunchKernelGGL(rcpValueK, dim3(gridsize), dim3(bsize), 0, 0, d_array, length); return 0; } //------------------------------------------------------------------------------ // Kernel for scale //------------------------------------------------------------------------------ __global__ static void scaleValueK(CeedScalar *__restrict__ x, CeedScalar alpha, CeedInt size) { int idx = threadIdx.x + blockDim.x * blockIdx.x; if (idx >= size) return; x[idx] *= alpha; } //------------------------------------------------------------------------------ // Compute x = alpha x on device //------------------------------------------------------------------------------ extern "C" int CeedDeviceScale_Hip(CeedScalar *x_array, CeedScalar alpha, CeedInt length) { const int bsize = 512; const int vecsize = length; int gridsize = vecsize / bsize; if (bsize * gridsize < vecsize) gridsize += 1; hipLaunchKernelGGL(scaleValueK, dim3(gridsize), dim3(bsize), 0, 0, x_array, alpha, length); return 0; } //------------------------------------------------------------------------------ // Kernel for axpy //------------------------------------------------------------------------------ __global__ static void axpyValueK(CeedScalar *__restrict__ y, CeedScalar alpha, CeedScalar *__restrict__ x, CeedInt size) { int idx = threadIdx.x + blockDim.x * blockIdx.x; if (idx >= size) return; y[idx] += alpha * x[idx]; } //------------------------------------------------------------------------------ // Compute y = alpha x + y on device //------------------------------------------------------------------------------ extern "C" int CeedDeviceAXPY_Hip(CeedScalar *y_array, CeedScalar alpha, CeedScalar *x_array, CeedInt length) { const int bsize = 512; const int vecsize = length; int gridsize = vecsize / bsize; if (bsize * gridsize < vecsize) gridsize += 1; hipLaunchKernelGGL(axpyValueK, dim3(gridsize), dim3(bsize), 0, 0, y_array, alpha, x_array, length); return 0; } //------------------------------------------------------------------------------ // Kernel for axpby //------------------------------------------------------------------------------ __global__ static void axpbyValueK(CeedScalar *__restrict__ y, CeedScalar alpha, CeedScalar beta, CeedScalar *__restrict__ x, CeedInt size) { int idx = threadIdx.x + blockDim.x * blockIdx.x; if (idx >= size) return; y[idx] = beta * y[idx]; y[idx] += alpha * x[idx]; } //------------------------------------------------------------------------------ // Compute y = alpha x + beta y on device //------------------------------------------------------------------------------ extern "C" int CeedDeviceAXPBY_Hip(CeedScalar *y_array, CeedScalar alpha, CeedScalar beta, CeedScalar *x_array, CeedInt length) { const int bsize = 512; const int vecsize = length; int gridsize = vecsize / bsize; if (bsize * gridsize < vecsize) gridsize += 1; hipLaunchKernelGGL(axpbyValueK, dim3(gridsize), dim3(bsize), 0, 0, y_array, alpha, beta, x_array, length); return 0; } //------------------------------------------------------------------------------ // Kernel for pointwise mult //------------------------------------------------------------------------------ __global__ static void pointwiseMultValueK(CeedScalar *__restrict__ w, CeedScalar *x, CeedScalar *__restrict__ y, CeedInt size) { int idx = threadIdx.x + blockDim.x * blockIdx.x; if (idx >= size) return; w[idx] = x[idx] * y[idx]; } //------------------------------------------------------------------------------ // Compute the pointwise multiplication w = x .* y on device //------------------------------------------------------------------------------ extern "C" int CeedDevicePointwiseMult_Hip(CeedScalar *w_array, CeedScalar *x_array, CeedScalar *y_array, CeedInt length) { const int bsize = 512; const int vecsize = length; int gridsize = vecsize / bsize; if (bsize * gridsize < vecsize) gridsize += 1; hipLaunchKernelGGL(pointwiseMultValueK, dim3(gridsize), dim3(bsize), 0, 0, w_array, x_array, y_array, length); return 0; }