//===----------------------------------------------------------------------===// // // Part of CUDASTF in CUDA C++ Core Libraries, // under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception // SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. // //===----------------------------------------------------------------------===// /** * @file * * @brief Freeze data in read-only fashion * */ #include #include using namespace cuda::experimental::stf; int X0(int i) { return 17 * i + 45; } __global__ void mult(slice s, int val) { int tid = blockIdx.x * blockDim.x + threadIdx.x; int nthreads = gridDim.x * blockDim.x; for (int i = tid; i < s.size(); i += nthreads) { s(i) *= val; } } int main() { stream_ctx ctx; cudaStream_t stream = ctx.pick_stream(); const int N = 16; int X[N]; for (int i = 0; i < N; i++) { X[i] = X0(i); } auto lX = ctx.logical_data(X).set_symbol("X"); auto lY = ctx.logical_data(lX.shape()).set_symbol("Y"); for (int k = 0; k < 4; k++) { auto fx = ctx.freeze(lX, access_mode::rw, data_place::current_device()); _CCCL_ASSERT(fx.get_access_mode() == access_mode::rw, "invalid access mode"); auto dX = fx.get(data_place::current_device(), stream); mult<<<8, 4, 0, stream>>>(dX, 4); fx.unfreeze(stream); ctx.parallel_for(lX.shape(), lX.read(), lY.write()).set_symbol("Y=X")->*[] __device__(size_t i, auto x, auto y) { y(i) = x(i); }; ctx.parallel_for(lX.shape(), lY.rw()).set_symbol("Y+=1")->*[] __device__(size_t i, auto y) { y(i) += 1; }; // ctx.host_launch(lX.read(), lY.read())->*[](auto x, auto y) { // for (int i = 0; i < x.size(); i++) { // EXPECT(x(i) == 2*X0(i) + 4); // } // // for (int i = 0; i < y.size(); i++) { // EXPECT(y(i) == 2*X0(i) + 4); // } // }; } ctx.finalize(); }