Add to ORKGMulticore computational accelerators such as Graphics Processor Units(GPUs) became common for gaining high-performance computing on a larger scale.Programming GPUs requires detailed knowledge of the underlying architecture in order to get maximum performance. In this paper we present solution of vector distance calculation on NVIDIA’s parallel computing architecture CUDA (Common Unified Device Architecture), where we optimize the performance of a parallel algorithm and get significant speedup
The programming of GPUs (Graphics Processing Units) is ready for practical applications; the largest...
Graphics processor units (GPU) that are originally designed for graphics rendering have emerged as m...
The aim of the thesis is implementation of certain algorithms in computational geometry on the CUDA ...
The ever-increasing size of data sets and the need for real-time processing drives the need for high...
Distance-to-Default(DTD), which is used to describe the default risk of a rm, acts an important role...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
Abstract — GPU based on CUDA Architecture developed by NVIDIA is a high performance computing device...
Nearest neighbor analysis is one of the classic methods to find out the tendency of the observed poi...
In many research fields the numerical problems demand extremely large computational power. As a c...
International audienceWe present a GPU implementation in C and CUDA of a matrix-by-vector procedure ...
In this work, we introduce real time image processing techniques using modern programmable Graphic P...
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Since the first version of CUDA was launch, many improvements were made in GPU computing. Every new ...
This work shows that it is possible to obtain faster MPI image reconstructions by implementing the a...
The programming of GPUs (Graphics Processing Units) is ready for practical applications; the largest...
Graphics processor units (GPU) that are originally designed for graphics rendering have emerged as m...
The aim of the thesis is implementation of certain algorithms in computational geometry on the CUDA ...
The ever-increasing size of data sets and the need for real-time processing drives the need for high...
Distance-to-Default(DTD), which is used to describe the default risk of a rm, acts an important role...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
Abstract — GPU based on CUDA Architecture developed by NVIDIA is a high performance computing device...
Nearest neighbor analysis is one of the classic methods to find out the tendency of the observed poi...
In many research fields the numerical problems demand extremely large computational power. As a c...
International audienceWe present a GPU implementation in C and CUDA of a matrix-by-vector procedure ...
In this work, we introduce real time image processing techniques using modern programmable Graphic P...
This thesis report is submitted in partial fulfilment of the requirements for the degree of Bachelor...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
Since the first version of CUDA was launch, many improvements were made in GPU computing. Every new ...
This work shows that it is possible to obtain faster MPI image reconstructions by implementing the a...
The programming of GPUs (Graphics Processing Units) is ready for practical applications; the largest...
Graphics processor units (GPU) that are originally designed for graphics rendering have emerged as m...
The aim of the thesis is implementation of certain algorithms in computational geometry on the CUDA ...