Maneesh Gupta
75 строки
3.3 KiB
C++
75 строки
3.3 KiB
C++
/*
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Copyright (c) 2015-2016 Advanced Micro Devices, Inc. All rights reserved.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.
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*/
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// Simple test showing how to use C++AMP syntax with array_view.
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// The code uses AMP's array_view class, which provides automatic data synchronization
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// of data between the host and the accelerator. As noted below, the HCC runtime
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// will automatically copy data to and from the host, without the user needing
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// to manually perform such copies. This is an excellent mode for developers
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// new to GPU programming and matches the memory models provided by recent systems where
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// CPU and GPU share the same memory pool. Advanced programmers may prefer
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// more explicit control over the data movement - shown in the other vadd_hc_array and
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// vadd_hc_am examples.
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// This example shows the similarity between C++AMP and and HC for simple cases where
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// implicit data transfer is used - really the only difference is the namespace.
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// Other examples show some of the more advanced controls.
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#include <amp.h>
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int main(int argc, char* argv[]) {
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int sizeElements = 1000000;
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bool pass = true;
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// Allocate auto-managed host/device views of data:
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concurrency::array_view<float> A(sizeElements);
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concurrency::array_view<float> B(sizeElements);
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concurrency::array_view<float> C(sizeElements);
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// Initialize host data
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for (int i = 0; i < sizeElements; i++) {
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A[i] = 1.618f * i;
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B[i] = 3.142f * i;
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}
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C.discard_data(); // tell runtime not to copy CPU host data.
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// Launch kernel onto default accelerator
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// The HCC runtime will ensure that A and B are available on the accelerator before launching
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// the kernel.
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concurrency::parallel_for_each(concurrency::extent<1>(sizeElements),
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[=](concurrency::index<1> idx) restrict(amp) {
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int i = idx[0];
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C[i] = A[i] + B[i];
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});
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for (int i = 0; i < sizeElements; i++) {
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float ref = 1.618f * i + 3.142f * i;
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// Because C is an array_view, the HCC runtime will copy C back to host at first access
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// here:
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if (C[i] != ref) {
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printf("error:%d computed=%6.2f, reference=%6.2f\n", i, C[i], ref);
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pass = false;
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}
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};
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if (pass) printf("PASSED!\n");
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}
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