# Dgemv

Intel MKL provides several routines for multiplying matrices. The most widely used is the

Routines available in GSL; GSL is Free Software; Obtaining GSL; No Warranty My CPU is i7-4790 and I tested dgemv with m=6400, n=64 but the highest performance was only 6.9GFLOPS when using 4 or 8 threads. f06paf (dgemv) performs one of the matrix-vector operations y ← α A x + β y , or y ← α A T x + β y , where A is an m by n real matrix, x and y are real vectors, and α and β are real scalars. This modified text is an extract of the original Stack Overflow Documentation created by following contributors and released under CC BY-SA 3.0 Apr 13, 2018 · Problems begin when the c++-code makes use of some other libraries, e.g., armadillo or whorp, which behind the scene make calls to system's BLAS/LAPACK routines. POL-DGEMV is implemented with unrolling and data fetching in advance similar to algorithmic prefetching as described in Agarwal et al. GEMM-Based Level 3 BLAS: High-Performance Model Implementations and Performance Evaluation Benchmark Daxpy and dgemv are memory- bound as expected, reaching about 95% and 90% of the peak.

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The leading dimension must be greater than or equal to 1 and greater than or equal to the value specified in m. x The heart of my simulation is the construction of a 2d tensor and then multiplication of that tensor by a vector. In the past, I was certain that execution time was going to be dominated by construction of the tensor, which is O(n^2) and fairly involved. MUCH to my surprise, I discovered after using cudaprof that my program spends slightly more time in dgemv_main! This is a huge surprise to me Arduino Stack Exchange is a question and answer site for developers of open-source hardware and software that is compatible with Arduino.

## * * Purpose * ===== * * DGEMV performs one of the matrix-vector operations * * y := alpha*A*x + beta*y, or y := alpha*A**T*x + beta*y, * * where alpha and beta are scalars, x and y are vectors and A is an * m by n matrix.

Active 5 years, 11 months ago. Viewed 6k times 4. 2.

### SGEMV and DGEMV are Level 2 BLAS subroutines. It is suggested that these subroutines be used instead of SGEMX, DGEMX, SGEMTX, and DGEMTX, which are provided only for compatibility with earlier releases of ESSL. On certain processors, SIMD algorithms may be used if alignment requirements are met.

incx.

dgemv NAME DGEMV - perform one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A'*x + beta*y, SYNOPSIS SUBROUTINE DGEMV ( TRANS, M, N, ALPHA, A, LDA, X, INCX, BETA, Y, INCY ) DOUBLE PRECISION ALPHA, BETA INTEGER INCX, INCY, LDA, M, N CHARACTER*1 TRANS DOUBLE PRECISION A( LDA, * ), X( * ), Y( * ) PURPOSE DGEMV performs one of the matrix-vector operations where alpha and PURPOSE dgemv performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A'*x + beta*y, where alpha and beta are scalars, x and y are vectors and A is an m by n matrix. SGEMV and DGEMV are Level 2 BLAS subroutines. It is suggested that these subroutines be used instead of SGEMX, DGEMX, SGEMTX, and DGEMTX, which are provided only for compatibility with earlier releases of ESSL. On certain processors, SIMD algorithms may be used if alignment requirements are met.

TRANS - CHARACTER*1. On entry, TRANS specifies the operation to be performed as follows: TRANS = 'N' or 'n' y := alpha*A*x + beta*y. Matrix-vector product with dgemm/dgemv. Ask Question Asked 5 years, 11 months ago. Active 5 years, 11 months ago. Viewed 6k times 4.

Using this interface also allows you to omit offset and leading dimension arguments. However, because of these conversions, these routines dgemm NAME DGEMM - perform one of the matrix-matrix operations C := alpha*op( A )*op( B ) + beta*C, SYNOPSIS SUBROUTINE DGEMM ( TRANSA, TRANSB, M, N, K, ALPHA, A, LDA, B, LDB, BETA, C, LDC ) CHARACTER*1 TRANSA, TRANSB INTEGER M, N, K, LDA, LDB, LDC DOUBLE PRECISION ALPHA, BETA DOUBLE PRECISION A( LDA, * ), B( LDB, * ), C( LDC, * ) PURPOSE … dgemv (3p) Name. dgemv - vector operations y := alpha*A*x + beta*y or y := alpha*A'*x + beta*y. Synopsis SUBROUTINE DGEMV(TRANSA, M, N, ALPHA, A, LDA, X, INCX, BETA # DGEMV performs one of the matrix-vector operations # y := alpha*A*x + beta*y, or y := alpha*A'*x + beta*y, # where alpha and beta are scalars, x and y are vectors and A is an Nov 14, 2017 DOUBLE PRECISION for dgemv. COMPLEX for cgemv, scgemv. DOUBLE COMPLEX for zgemv, dzgemv.

Dgemm is compute-bound for all sizes reaching also about 95% of the peak p. Note that the FFT is plotted with measured flops and not with pseudo- flops (fixing the op count to 5n log (n), an overestimation), as commonly done. See full list on nsc.liu.se Stephen, >No, but the machine could easily have overheated. It's been pretty warm >where I live lately.

Ask Question Asked 5 years, 11 months ago. Active 5 years, 11 months ago. Viewed 6k times 4. 2. Using Lapack with C++ is giving me a small headache.

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### The Intel Math Kernel Library (MKL) is a library of optimized, general-purpose math software. The routines are optimized and threaded, and CISL recommends

dgemv NAME DGEMV - perform one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A'*x + beta*y, SYNOPSIS SUBROUTINE DGEMV ( TRANS, M, N, ALPHA, A, LDA, X, INCX, BETA, Y, INCY ) DOUBLE PRECISION ALPHA, BETA INTEGER INCX, INCY, LDA, M, N CHARACTER*1 TRANS DOUBLE PRECISION A( LDA, * ), X( * ), Y( * ) PURPOSE DGEMV performs one of the matrix-vector operations where alpha and PURPOSE dgemv performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A'*x + beta*y, where alpha and beta are scalars, x and y are vectors and A is an m by n matrix. SGEMV and DGEMV are Level 2 BLAS subroutines. It is suggested that these subroutines be used instead of SGEMX, DGEMX, SGEMTX, and DGEMTX, which are provided only for compatibility with earlier releases of ESSL. On certain processors, SIMD algorithms may be used if alignment requirements are met. DGEMV performs one of the matrix-vector operations where alpha and beta are scalars, x and y are vectors and A is an m by n matrix. Arguments * * Purpose * ===== * * DGEMV performs one of the matrix-vector operations * * y := alpha*A*x + beta*y, or y := alpha*A**T*x + beta*y, * * where alpha and beta are scalars, x and y are vectors and A is an * m by n matrix. Matrix-vector product with dgemm/dgemv.

## I want to test Intel MKL matrix multiplication, So I include and I just use the cblas_dgemm function, but it always says undefined reference to `cblas_dgemm' I also link the -lmkl_core -

COMPLEX for cgemv, scgemv. DOUBLE COMPLEX for zgemv, dzgemv. Array, DIMENSION at least (1+(n-1)*abs(incx)) when trans = 'N' or 'n' and at least (1+(m - 1)*abs(incx)) otherwise. Before entry, the incremented array x must contain the vector x. incx. INTEGER.

While this paper discusses primarily Kepler Apr 06, 2015 Problems begin when the c++-code makes use of some other libraries, e.g., armadillo or whorp, which behind the scene make calls to system's BLAS/LAPACK routines. May 06, 2020 Arduino Stack Exchange is a question and answer site for developers of open-source hardware and software that is compatible with Arduino. It only takes a minute to sign up. reference to 'wrapper2_dgemv_ 'undefined and one warning that I can not fix: `is deprecated: publishing an unique_ptr is prefered when using intra process communication. If using a shared_ptr, use publish(*msg). [-Wdeprecated-declarations`] is the input matrix of float (for sgemv) or double (for dgemv) values lda is the leading dimension of the array specified by a.