From 483eb2f56657e8e7f419ab1a4fab8dce9ade8609 Mon Sep 17 00:00:00 2001 From: Daniel Baumann Date: Sat, 27 Apr 2024 20:24:20 +0200 Subject: Adding upstream version 14.2.21. Signed-off-by: Daniel Baumann --- .../libs/compute/example/batched_determinant.cpp | 96 ++++++++++++++++++++++ 1 file changed, 96 insertions(+) create mode 100644 src/boost/libs/compute/example/batched_determinant.cpp (limited to 'src/boost/libs/compute/example/batched_determinant.cpp') diff --git a/src/boost/libs/compute/example/batched_determinant.cpp b/src/boost/libs/compute/example/batched_determinant.cpp new file mode 100644 index 00000000..0029151e --- /dev/null +++ b/src/boost/libs/compute/example/batched_determinant.cpp @@ -0,0 +1,96 @@ +//---------------------------------------------------------------------------// +// Copyright (c) 2013-2014 Kyle Lutz +// +// Distributed under the Boost Software License, Version 1.0 +// See accompanying file LICENSE_1_0.txt or copy at +// http://www.boost.org/LICENSE_1_0.txt +// +// See http://boostorg.github.com/compute for more information. +//---------------------------------------------------------------------------// + +#include + +#include +#include + +#include +#include +#include +#include +#include + +namespace compute = boost::compute; + +// this example shows how to compute the determinant of many 4x4 matrices +// using a determinant function and the transform() algorithm. in OpenCL the +// float16 type can be used to store a 4x4 matrix and the components are laid +// out in the following order: +// +// M = [ s0 s4 s8 sc ] +// [ s1 s5 s9 sd ] +// [ s2 s6 sa se ] +// [ s3 s7 sb sf ] +// +// the input matrices are created using eigen's random matrix and then +// used again at the end to verify the results of the determinant function. +int main() +{ + // get default device and setup context + compute::device gpu = compute::system::default_device(); + compute::context context(gpu); + compute::command_queue queue(context, gpu); + std::cout << "device: " << gpu.name() << std::endl; + + size_t n = 1000; + + // create random 4x4 matrices on the host + std::vector matrices(n); + for(size_t i = 0; i < n; i++){ + matrices[i] = Eigen::Matrix4f::Random(); + } + + // copy matrices to the device + using compute::float16_; + compute::vector input(n, context); + compute::copy( + matrices.begin(), matrices.end(), input.begin(), queue + ); + + // function returning the determinant of a 4x4 matrix. + BOOST_COMPUTE_FUNCTION(float, determinant4x4, (const float16_ m), + { + return m.s0*m.s5*m.sa*m.sf + m.s0*m.s6*m.sb*m.sd + m.s0*m.s7*m.s9*m.se + + m.s1*m.s4*m.sb*m.se + m.s1*m.s6*m.s8*m.sf + m.s1*m.s7*m.sa*m.sc + + m.s2*m.s4*m.s9*m.sf + m.s2*m.s5*m.sb*m.sc + m.s2*m.s7*m.s8*m.sd + + m.s3*m.s4*m.sa*m.sd + m.s3*m.s5*m.s8*m.se + m.s3*m.s6*m.s9*m.sc - + m.s0*m.s5*m.sb*m.se - m.s0*m.s6*m.s9*m.sf - m.s0*m.s7*m.sa*m.sd - + m.s1*m.s4*m.sa*m.sf - m.s1*m.s6*m.sb*m.sc - m.s1*m.s7*m.s8*m.se - + m.s2*m.s4*m.sb*m.sd - m.s2*m.s5*m.s8*m.sf - m.s2*m.s7*m.s9*m.sc - + m.s3*m.s4*m.s9*m.se - m.s3*m.s5*m.sa*m.sc - m.s3*m.s6*m.s8*m.sd; + }); + + // calculate determinants on the gpu + compute::vector determinants(n, context); + compute::transform( + input.begin(), input.end(), determinants.begin(), determinant4x4, queue + ); + + // check determinants + std::vector host_determinants(n); + compute::copy( + determinants.begin(), determinants.end(), host_determinants.begin(), queue + ); + + for(size_t i = 0; i < n; i++){ + float det = matrices[i].determinant(); + + if(std::abs(det - host_determinants[i]) > 1e-6){ + std::cerr << "error: wrong determinant at " << i << " (" + << host_determinants[i] << " != " << det << ")" + << std::endl; + return -1; + } + } + + return 0; +} -- cgit v1.2.3