This paper presents a fast and robust approach to evaluate the singular values of a very large number of small matrices on GPUs. The timings and the accuracy obtained are compared to those achieved by "state-of-the-art" libraries. The results show that, by suitably tuning the trade-off between computational speed and accuracy, a reasonable speedup over a fast multi-core CPU is possible
General matrix-matrix multiplications (GEMM) in vendor-supplied BLAS libraries are best optimized fo...
General matrix-matrix multiplications with double-precision real and complex entries (DGEMM and ZGEM...
An algorithm for computing the singular values of a complex matrix based on Rijk's improvement of th...
This paper presents a fast and robust approach to evaluate the singular values of a very large numbe...
Abstract. Approximation of matrices using the Singular Value Decom-position (SVD) plays a central ro...
We present several algorithms to compute the solution of a linear system of equations on a graphics ...
We provide efficient single- and double-precision GPU (Graphics Processing Unit) implementa-tions of...
We present an interface and an implementation of the General Matrix Multiply (GEMM) routine for mult...
Linear algebra algorithms are fundamental to many com-puting applications. Modern GPUs are suited fo...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
In this paper we discuss about our experiences in improving the performance of two key algorithms: t...
We analyze when it is possible to compute the singular values and singular vectors of a matrix with ...
International audienceThis paper focuses on the resolution of a large number of small symmetric line...
Abstract: Few realize that, for large matrices, many dense matrix computations achieve nearly the sa...
The goal of this survey is to give a view of the state-of-the-art of computing the Singular Value De...
General matrix-matrix multiplications (GEMM) in vendor-supplied BLAS libraries are best optimized fo...
General matrix-matrix multiplications with double-precision real and complex entries (DGEMM and ZGEM...
An algorithm for computing the singular values of a complex matrix based on Rijk's improvement of th...
This paper presents a fast and robust approach to evaluate the singular values of a very large numbe...
Abstract. Approximation of matrices using the Singular Value Decom-position (SVD) plays a central ro...
We present several algorithms to compute the solution of a linear system of equations on a graphics ...
We provide efficient single- and double-precision GPU (Graphics Processing Unit) implementa-tions of...
We present an interface and an implementation of the General Matrix Multiply (GEMM) routine for mult...
Linear algebra algorithms are fundamental to many com-puting applications. Modern GPUs are suited fo...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
In this paper we discuss about our experiences in improving the performance of two key algorithms: t...
We analyze when it is possible to compute the singular values and singular vectors of a matrix with ...
International audienceThis paper focuses on the resolution of a large number of small symmetric line...
Abstract: Few realize that, for large matrices, many dense matrix computations achieve nearly the sa...
The goal of this survey is to give a view of the state-of-the-art of computing the Singular Value De...
General matrix-matrix multiplications (GEMM) in vendor-supplied BLAS libraries are best optimized fo...
General matrix-matrix multiplications with double-precision real and complex entries (DGEMM and ZGEM...
An algorithm for computing the singular values of a complex matrix based on Rijk's improvement of th...