NVIDIA have released a new platform (CUDA) for general purpose computing on their graphical processing units (GPU). This paper evaluates use of this platform for statistical machine learning applications. The transfer rates to and from the GPU are measured, as is the performance of matrix vector operations on the GPU. An implementation of a sparse matrix vector product on the GPU is outlined and evaluated. Performance comparisons are made with the host processor
Abstract—CUDA programmed GPUs are rapidly becoming a major choice in high performance com-puting and...
Over the past few years, we have seen an exponential performance boost of the graphics processing un...
Using modern graphics processing units for no-graphics high performance computing is motivated by th...
Abstract. NVIDIA have released a new platform (CUDA) for general purpose computing on their graphica...
Context. Machine Learning is a complex and resource consuming process that requires a lot of computi...
Using modern Graphic Processing Units (GPUs) becomes very useful for computing complex and time cons...
Open-source deep learning tools has been distributed numerously and has gain popularity in the past ...
The Graphics Processing Unit (GPU) parallel architecture is now being used not just for graphics but...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
Graphics processing units (GPUs) were originally used solely for the purpose of graph- ics rendering...
As time has passed, the general purpose programming paradigm has evolved, producing different hardw...
Abstract—In this paper, we construe key factors in design and evaluation of image processing algorit...
Abstract — GPU based on CUDA Architecture developed by NVIDIA is a high performance computing device...
A graphical processing unit (GPU) is a hardware device normally used to manipulate computer memory f...
In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multip...
Abstract—CUDA programmed GPUs are rapidly becoming a major choice in high performance com-puting and...
Over the past few years, we have seen an exponential performance boost of the graphics processing un...
Using modern graphics processing units for no-graphics high performance computing is motivated by th...
Abstract. NVIDIA have released a new platform (CUDA) for general purpose computing on their graphica...
Context. Machine Learning is a complex and resource consuming process that requires a lot of computi...
Using modern Graphic Processing Units (GPUs) becomes very useful for computing complex and time cons...
Open-source deep learning tools has been distributed numerously and has gain popularity in the past ...
The Graphics Processing Unit (GPU) parallel architecture is now being used not just for graphics but...
Modern graphics processing units (GPUs) have been at the leading edge of in-creasing chip-level para...
Graphics processing units (GPUs) were originally used solely for the purpose of graph- ics rendering...
As time has passed, the general purpose programming paradigm has evolved, producing different hardw...
Abstract—In this paper, we construe key factors in design and evaluation of image processing algorit...
Abstract — GPU based on CUDA Architecture developed by NVIDIA is a high performance computing device...
A graphical processing unit (GPU) is a hardware device normally used to manipulate computer memory f...
In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multip...
Abstract—CUDA programmed GPUs are rapidly becoming a major choice in high performance com-puting and...
Over the past few years, we have seen an exponential performance boost of the graphics processing un...
Using modern graphics processing units for no-graphics high performance computing is motivated by th...