To deal with the massive computation workload between matrix multiplication, we developed a calculation procedure to speed up the maximum covariance analysis between two huge matrix using the GPU instead of CPU. And the attachment includes configuration guidance of GPU driver, CUDA, gputools in R, and calculation and visualization codes of MCA in R
As users and developers, we are witnessing the opening of a new computing scenario: the introduction...
This paper discusses different approaches for computing the Walsh spectra on graphics processor unit...
Recent advances in high-throughput genomic technology, such as micro arrays, usually produce vast am...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
© 2019, Pleiades Publishing, Ltd. Practical applicability of many statistical algorithms is limited ...
This paper presents initial experiments in implementing two notable matrix multiplication algorithms...
Multiphysics systems are used to simulate various physics phenomena given byPartial Differential Equ...
We provide efficient single- and double-precision GPU (Graphics Processing Unit) implementa-tions of...
Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using S...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
Graphics hardware's performance is advancing much faster than the performance of conventional microp...
The article describes the matrix algebra libraries based on the modern technologies of parallel prog...
In order to utilize the tremendous computing power of grpahics hardware and to automatically adapt t...
Abstract We present an interface to the graphics processing unit (GPU) from MATLAB, and four algorit...
Graphics hardware’s performance is advancing much faster than the performance of conventional microp...
As users and developers, we are witnessing the opening of a new computing scenario: the introduction...
This paper discusses different approaches for computing the Walsh spectra on graphics processor unit...
Recent advances in high-throughput genomic technology, such as micro arrays, usually produce vast am...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
© 2019, Pleiades Publishing, Ltd. Practical applicability of many statistical algorithms is limited ...
This paper presents initial experiments in implementing two notable matrix multiplication algorithms...
Multiphysics systems are used to simulate various physics phenomena given byPartial Differential Equ...
We provide efficient single- and double-precision GPU (Graphics Processing Unit) implementa-tions of...
Latent Semantic Analysis (LSA) aims to reduce the dimensions of large term-document datasets using S...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
Graphics hardware's performance is advancing much faster than the performance of conventional microp...
The article describes the matrix algebra libraries based on the modern technologies of parallel prog...
In order to utilize the tremendous computing power of grpahics hardware and to automatically adapt t...
Abstract We present an interface to the graphics processing unit (GPU) from MATLAB, and four algorit...
Graphics hardware’s performance is advancing much faster than the performance of conventional microp...
As users and developers, we are witnessing the opening of a new computing scenario: the introduction...
This paper discusses different approaches for computing the Walsh spectra on graphics processor unit...
Recent advances in high-throughput genomic technology, such as micro arrays, usually produce vast am...
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