Modern graphics hardware is well suited to highly parallel nu-merical tasks and provides significant cost and performance benefits. Graphics hardware vendors are now making avail-able development tools to support high performance comput-ing. NVIDIA’S CUDAplatform, in particular, offers direct access to graphics hardware through a programming language similar to C. Using the CUDA platform we have implemented a Dirac-Wilson operator which runs at an effective 68 Gigaflops on the Tesla C870 GPU. The recently released GTX 280 GPU runs this same code at 92 Gigaflops and we expect improvement pending code optimization.
GPUs, Graphics Processing Units, offer a large amount of processing power by providing a platform fo...
Generating fully 3D terrains is a dificult task, meaning that we need to store a lot of data or do a...
This research study is based on the growing interest towards graphical processing unit usability for...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
In many research fields the numerical problems demand extremely large computational power. As a c...
Over the past few years, we have seen an exponential performance boost of the graphics processing un...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
Product data parallel GPU processor has recently attracted many application developers attention. GP...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
Recent advances in GPUs opened a new opportunity in harnessing their computing power for general pur...
Since the first version of CUDA was launch, many improvements were made in GPU computing. Every new ...
Just five years ago, NVIDIA introduced CUDA, the Compute Unified Device Architecture, which signifi...
The current powerful graphics cards, providing stunning real-time visual effects for computer-based ...
Abstract — Scientific computation requires a great amount of computing power especially in floating...
GPUs, Graphics Processing Units, offer a large amount of processing power by providing a platform fo...
Generating fully 3D terrains is a dificult task, meaning that we need to store a lot of data or do a...
This research study is based on the growing interest towards graphical processing unit usability for...
GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GP...
In many research fields the numerical problems demand extremely large computational power. As a c...
Over the past few years, we have seen an exponential performance boost of the graphics processing un...
The future of computation is the GPU, i.e. the Graphical Processing Unit. The graphics cards have sh...
Graphic processors are becoming faster and faster. Computational power within graphic processing uni...
Product data parallel GPU processor has recently attracted many application developers attention. GP...
AbstractGraphics processor units (GPUs) have evolved to handle throughput oriented workloads where a...
Recent advances in GPUs opened a new opportunity in harnessing their computing power for general pur...
Since the first version of CUDA was launch, many improvements were made in GPU computing. Every new ...
Just five years ago, NVIDIA introduced CUDA, the Compute Unified Device Architecture, which signifi...
The current powerful graphics cards, providing stunning real-time visual effects for computer-based ...
Abstract — Scientific computation requires a great amount of computing power especially in floating...
GPUs, Graphics Processing Units, offer a large amount of processing power by providing a platform fo...
Generating fully 3D terrains is a dificult task, meaning that we need to store a lot of data or do a...
This research study is based on the growing interest towards graphical processing unit usability for...