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Added warp::shfl functionality. #1273
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205666b
Added warp::shfl functionality.
frobnitzem beec8c2
removed unused param in Shfl<WarpSingleThread>
frobnitzem 8b68865
Specified 32-bit precision ints on shfl() and added width parameter.
frobnitzem 70f01ba
Compared float by error tolerance to avoid compiler warning.
frobnitzem 5f4e89f
remove magic number
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| Original file line number | Diff line number | Diff line change |
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| /* Copyright 2021 David M. Rogers | ||
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| * | ||
| * This file is part of Alpaka. | ||
| * | ||
| * This Source Code Form is subject to the terms of the Mozilla Public | ||
| * License, v. 2.0. If a copy of the MPL was not distributed with this | ||
| * file, You can obtain one at http://mozilla.org/MPL/2.0/. | ||
| */ | ||
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| #include <alpaka/test/KernelExecutionFixture.hpp> | ||
| #include <alpaka/test/acc/TestAccs.hpp> | ||
| #include <alpaka/test/queue/Queue.hpp> | ||
| #include <alpaka/warp/Traits.hpp> | ||
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| #include <catch2/catch.hpp> | ||
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| #include <cstdint> | ||
| #include <limits> | ||
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| //############################################################################# | ||
| class ShflSingleThreadWarpTestKernel | ||
| { | ||
| public: | ||
| //------------------------------------------------------------------------- | ||
| ALPAKA_NO_HOST_ACC_WARNING | ||
| template<typename TAcc> | ||
| ALPAKA_FN_ACC auto operator()(TAcc const& acc, bool* success) const -> void | ||
| { | ||
| std::int32_t const warpExtent = alpaka::warp::getSize(acc); | ||
| ALPAKA_CHECK(*success, warpExtent == 1); | ||
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| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, 12, 0) == 12); | ||
| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, 42, -1) == 42); | ||
| float ans = alpaka::warp::shfl(acc, 3.3f, 0); | ||
| ALPAKA_CHECK(*success, alpaka::math::abs(acc, ans - 3.3f) < 1e-8f); | ||
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| } | ||
| }; | ||
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| //############################################################################# | ||
| class ShflMultipleThreadWarpTestKernel | ||
| { | ||
| public: | ||
| //----------------------------------------------------------------------------- | ||
| ALPAKA_NO_HOST_ACC_WARNING | ||
| template<typename TAcc> | ||
| ALPAKA_FN_ACC auto operator()(TAcc const& acc, bool* success) const -> void | ||
| { | ||
| auto const localThreadIdx = alpaka::getIdx<alpaka::Block, alpaka::Threads>(acc); | ||
| auto const blockExtent = alpaka::getWorkDiv<alpaka::Block, alpaka::Threads>(acc); | ||
| std::int32_t const warpExtent = alpaka::warp::getSize(acc); | ||
| // Test relies on having a single warp per thread block | ||
| ALPAKA_CHECK(*success, static_cast<std::int32_t>(blockExtent.prod()) == warpExtent); | ||
| auto const threadIdxInWarp = std::int32_t(alpaka::mapIdx<1u>(localThreadIdx, blockExtent)[0]); | ||
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| ALPAKA_CHECK(*success, warpExtent > 1); | ||
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| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, 42, 0) == 42); | ||
| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, threadIdxInWarp, 0) == 0); | ||
| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, threadIdxInWarp, 1) == 1); | ||
| // Note the CUDA and HIP API-s differ on lane wrapping, but both agree it should not segfault | ||
| // https://github.com/ROCm-Developer-Tools/HIP-CPU/issues/14 | ||
| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, 5, -1) == 5); | ||
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| auto const epsilon = std::numeric_limits<float>::epsilon(); | ||
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| // Test various widths | ||
| for(int width = 1; width < warpExtent; width *= 2) | ||
| { | ||
| for(int idx = 0; idx < width; idx++) | ||
| { | ||
| int const off = width * (threadIdxInWarp / width); | ||
| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, threadIdxInWarp, idx, width) == idx + off); | ||
| float const ans = alpaka::warp::shfl(acc, 4.0f - float(threadIdxInWarp), idx, width); | ||
| float const expect = 4.0f - float(idx + off); | ||
| ALPAKA_CHECK(*success, alpaka::math::abs(acc, ans - expect) < epsilon); | ||
| } | ||
| } | ||
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| // Some threads quit the kernel to test that the warp operations | ||
| // properly operate on the active threads only | ||
| if(threadIdxInWarp >= warpExtent / 2) | ||
| return; | ||
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| for(int idx = 0; idx < warpExtent / 2; idx++) | ||
| { | ||
| ALPAKA_CHECK(*success, alpaka::warp::shfl(acc, threadIdxInWarp, idx) == idx); | ||
| float const ans = alpaka::warp::shfl(acc, 4.0f - float(threadIdxInWarp), idx); | ||
| float const expect = 4.0f - float(idx); | ||
| ALPAKA_CHECK(*success, alpaka::math::abs(acc, ans - expect) < epsilon); | ||
| } | ||
| } | ||
| }; | ||
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| //----------------------------------------------------------------------------- | ||
| TEMPLATE_LIST_TEST_CASE("shfl", "[warp]", alpaka::test::TestAccs) | ||
| { | ||
| using Acc = TestType; | ||
| using Dev = alpaka::Dev<Acc>; | ||
| using Pltf = alpaka::Pltf<Dev>; | ||
| using Dim = alpaka::Dim<Acc>; | ||
| using Idx = alpaka::Idx<Acc>; | ||
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| Dev const dev(alpaka::getDevByIdx<Pltf>(0u)); | ||
| auto const warpExtent = alpaka::getWarpSize(dev); | ||
| if(warpExtent == 1) | ||
| { | ||
| Idx const gridThreadExtentPerDim = 4; | ||
| alpaka::test::KernelExecutionFixture<Acc> fixture(alpaka::Vec<Dim, Idx>::all(gridThreadExtentPerDim)); | ||
| ShflSingleThreadWarpTestKernel kernel; | ||
| REQUIRE(fixture(kernel)); | ||
| } | ||
| else | ||
| { | ||
| // Work around gcc 7.5 trying and failing to offload for OpenMP 4.0 | ||
| #if BOOST_COMP_GNUC && (BOOST_COMP_GNUC == BOOST_VERSION_NUMBER(7, 5, 0)) && defined ALPAKA_ACC_ANY_BT_OMP5_ENABLED | ||
| return; | ||
| #else | ||
| using ExecutionFixture = alpaka::test::KernelExecutionFixture<Acc>; | ||
| auto const gridBlockExtent = alpaka::Vec<Dim, Idx>::all(2); | ||
| // Enforce one warp per thread block | ||
| auto blockThreadExtent = alpaka::Vec<Dim, Idx>::ones(); | ||
| blockThreadExtent[0] = static_cast<Idx>(warpExtent); | ||
| auto const threadElementExtent = alpaka::Vec<Dim, Idx>::ones(); | ||
| auto workDiv = typename ExecutionFixture::WorkDiv{gridBlockExtent, blockThreadExtent, threadElementExtent}; | ||
| auto fixture = ExecutionFixture{workDiv}; | ||
| ShflMultipleThreadWarpTestKernel kernel; | ||
| REQUIRE(fixture(kernel)); | ||
| #endif | ||
| } | ||
| } | ||
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IMO we need to add to the documentation that this function
shflis collective what means all threads need to call the function and also from the same code branch.The reason is that for CUDA the implementation is using
activemaskand for HIP all threads in a warp needs to call the function. Usingactivemaskmeans if threads from the if and else branch call the function they will not see each other.There was a problem hiding this comment.
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I updated these docs to include this warning.
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I think I forgot to add a similar warning to the previously existing warp collectives. You comment also alllies to those, right @psychocoderHPC ?
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@sbastrakov Yes this should be added to other warp functions too. Currently, only CUDA allows calling warp functions from different branches. It is fine if all threads of the warp are in the same branch but as soon as the threads diverge the behavior is undefined (for HIP and CUDA devices before sm_70) .