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Add performance monitoring for LLT
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@ -31,7 +31,6 @@ before-evaluators
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6845:7333ed40c6ef # change prefetching in gebp
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#6856:b5be5e10eb7f # merge index conversion
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6893:c3a64aba7c70 # clean blocking size computation
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6898:6fb31ebe6492 # rotating kernel for ARM
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6899:877facace746 # rotating kernel for ARM only
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#6904:c250623ae9fa # result_of
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6921:915f1b1fc158 # fix prefetching change for ARM
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@ -50,7 +49,7 @@ before-evaluators
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7098:b6f1db9cf9ec # Bug 992: don't select a 3p GEMM path with non-vectorizable scalar types, this hits unsupported paths in symm/triangular products code
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7591:09a8e2186610 # 3.3-alpha1
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7650:b0f3c8f43025 # help clang inlining
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8744:74b789ada92a # Improved the matrix multiplication blocking in the case where mr is not a power of 2 (e.g on Haswell CPUs)
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#8744:74b789ada92a # Improved the matrix multiplication blocking in the case where mr is not a power of 2 (e.g on Haswell CPUs)
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8789:efcb912e4356 # Made the index type a template parameter to evaluateProductBlockingSizes. Use numext::mini and numext::maxi instead of std::min/std::max to compute blocking sizes
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8972:81d53c711775 # Don't optimize the processing of the last rows of a matrix matrix product in cases that violate the assumptions made by the optimized code path
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8985:d935df21a082 # Remove the rotating kernel.
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@ -65,5 +64,5 @@ before-evaluators
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9942:b1d3eba60130 # Operators += and -= do not resize!
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9943:79bb9887afd4 # Ease compiler job to generate clean and efficient code in mat*vec
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9946:2213991340ea # Complete rewrite of column-major-matrix * vector product to deliver higher performance of modern CPU.
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9953:21acc0e8d782 # Improve performance of row-major-dense-matrix * vector products for recent CPUs.
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9955:630471c3298c # Improve performance of row-major-dense-matrix * vector products for recent CPUs. (this is the next changeset fixing a typo)
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@ -1,17 +1,4 @@
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#include <iostream>
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#include <fstream>
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#include <vector>
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#include <Eigen/Core>
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#include "../../BenchTimer.h"
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using namespace Eigen;
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#ifndef SCALAR
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#error SCALAR must be defined
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#endif
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typedef SCALAR Scalar;
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typedef Matrix<Scalar,Dynamic,Dynamic> Mat;
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#include "gemm_common.h"
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EIGEN_DONT_INLINE
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void gemm(const Mat &A, const Mat &B, Mat &C)
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@ -19,52 +6,7 @@ void gemm(const Mat &A, const Mat &B, Mat &C)
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C.noalias() += A * B;
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}
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EIGEN_DONT_INLINE
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double bench(long m, long n, long k)
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{
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Mat A(m,k);
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Mat B(k,n);
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Mat C(m,n);
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A.setRandom();
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B.setRandom();
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C.setZero();
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BenchTimer t;
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double up = 1e8*4/sizeof(Scalar);
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double tm0 = 4, tm1 = 10;
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if(NumTraits<Scalar>::IsComplex)
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{
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up /= 4;
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tm0 = 2;
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tm1 = 4;
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}
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double flops = 2. * m * n * k;
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long rep = std::max(1., std::min(100., up/flops) );
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long tries = std::max(tm0, std::min(tm1, up/flops) );
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BENCH(t, tries, rep, gemm(A,B,C));
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return 1e-9 * rep * flops / t.best();
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}
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int main(int argc, char **argv)
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{
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std::vector<double> results;
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std::string filename = std::string("gemm_settings.txt");
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if(argc>1)
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filename = std::string(argv[1]);
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std::ifstream settings(filename);
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long m, n, k;
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while(settings >> m >> n >> k)
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{
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//std::cerr << " Testing " << m << " " << n << " " << k << std::endl;
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results.push_back( bench(m, n, k) );
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}
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std::cout << RowVectorXd::Map(results.data(), results.size());
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return 0;
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return main_gemm(argc, argv, gemm);
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}
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66
bench/perf_monitoring/gemm/gemm_common.h
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66
bench/perf_monitoring/gemm/gemm_common.h
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@ -0,0 +1,66 @@
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#include <iostream>
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#include <fstream>
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#include <vector>
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#include <Eigen/Core>
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#include "../../BenchTimer.h"
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using namespace Eigen;
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#ifndef SCALAR
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#error SCALAR must be defined
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#endif
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typedef SCALAR Scalar;
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typedef Matrix<Scalar,Dynamic,Dynamic> Mat;
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template<typename Func>
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EIGEN_DONT_INLINE
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double bench(long m, long n, long k, const Func& f)
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{
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Mat A(m,k);
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Mat B(k,n);
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Mat C(m,n);
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A.setRandom();
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B.setRandom();
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C.setZero();
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BenchTimer t;
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double up = 1e8*4/sizeof(Scalar);
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double tm0 = 4, tm1 = 10;
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if(NumTraits<Scalar>::IsComplex)
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{
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up /= 4;
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tm0 = 2;
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tm1 = 4;
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}
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double flops = 2. * m * n * k;
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long rep = std::max(1., std::min(100., up/flops) );
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long tries = std::max(tm0, std::min(tm1, up/flops) );
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BENCH(t, tries, rep, f(A,B,C));
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return 1e-9 * rep * flops / t.best();
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}
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template<typename Func>
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int main_gemm(int argc, char **argv, const Func& f)
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{
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std::vector<double> results;
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std::string filename = std::string("gemm_settings.txt");
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if(argc>1)
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filename = std::string(argv[1]);
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std::ifstream settings(filename);
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long m, n, k;
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while(settings >> m >> n >> k)
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{
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//std::cerr << " Testing " << m << " " << n << " " << k << std::endl;
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results.push_back( bench(m, n, k, f) );
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}
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std::cout << RowVectorXd::Map(results.data(), results.size());
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return 0;
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}
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bench/perf_monitoring/gemm/gemm_square_settings.txt
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11
bench/perf_monitoring/gemm/gemm_square_settings.txt
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@ -0,0 +1,11 @@
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2400 2400 2400
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2463 2463 2463
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@ -47,14 +47,14 @@ double bench(long m, long n, Func &f)
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}
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template<typename Func>
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int main_gemv(int argc, char **argv, Func& f, const std::string &setting_filename)
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int main_gemv(int argc, char **argv, Func& f)
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{
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std::vector<double> results;
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std::string filename = std::string("gemv_settings.txt");
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if(argc>1)
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filename = std::string(argv[1]);
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std::ifstream settings(setting_filename);
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std::ifstream settings(filename);
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long m, n;
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while(settings >> m >> n)
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{
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bench/perf_monitoring/gemm/gemv_square_settings.txt
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bench/perf_monitoring/gemm/gemv_square_settings.txt
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@ -0,0 +1,13 @@
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102 102
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239 239
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2463 2463
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bench/perf_monitoring/gemm/llt.cpp
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15
bench/perf_monitoring/gemm/llt.cpp
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#include "gemm_common.h"
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#include <Eigen/Cholesky>
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EIGEN_DONT_INLINE
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void llt(const Mat &A, const Mat &B, Mat &C)
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{
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C = A;
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C.diagonal().array() += 1000;
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Eigen::internal::llt_inplace<Mat::Scalar, Lower>::blocked(C);
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}
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int main(int argc, char **argv)
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{
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return main_gemm(argc, argv, llt);
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}
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./run.sh trmv_lo gemv_square_settings.txt $*
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./run.sh trmv_upt gemv_square_settings.txt $*
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./run.sh trmv_lot gemv_square_settings.txt $*
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./run.sh llt gemm_square_settings.txt $*
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#include "gemv_common.h"
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EIGEN_DONT_INLINE
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void gemv(const Mat &A, Vec &B, const Vec &C)
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void trmv(const Mat &A, Vec &B, const Vec &C)
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{
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B.noalias() += A.transpose().triangularView<Lower>() * C;
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}
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