GPGPU

[...] High-Performance Graphics 2014 is the leading international forum for performance-oriented graphics and imaging [...]

[...] High-Performance Graphics is the leading international forum for performance-oriented graphics and imaging systems [...]

[...] implementations, languages, parallelism, compilers, hardware and architectures for high-performance graphics. The conference brings together researchers, engineers, and architects to discuss the [...]

[...] a stochastic simulation algorithm that efficiently reconstructs the temporal evolution of biological systems, modeled according to the stochastic formulation of chemical kinetics. The analysis of [...]

[...] a shift to the use of high-performance processors. In this work we present a simulator of biological systems, called cupSODA, which exploits the higher memory bandwidth and computational capability of [...]

[...] by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the [...]

[...] PCO 2014, the fourth Workshop on Parallel Computing and Optimization, will be held in conjunction with Symposium IEEE IPDPS, Phoenix, USA, May [...]

This master’s thesis by Markus Konrad analyzes the potentials of GPGPU on mobile devices such as smartphones or tablets. The question was, if an [...]

[...] and scientific computing in particular. All different applications of massively parallel computing in HEP will be addressed, from computational speed-ups in online and offline data selection [...]

[...] Hagihara: “Improving Cache Locality for GPU-based Volume Rendering”. Parallel Computing 40(5/6): 59-69, May 2014. [DOI]) [...]

[...] The course on Antenna Synthesis (with elements of GPU computing) is organized in the framework of the European School of Antennas. The course will take place [...]

[...] -to-use code fragments with a broad appeal to both developers and researchers interested in GPU computing. Authors interested in contributing to this volume are asked to submit a short proposal via [...]

[...] -to-use code fragments with a broad appeal to both developers and researchers interested in GPU computing. Researchers working on the development and implementation of methods for image and video [...]

[...] leading to reusable, adaptable and scalable code fragments. This book also serves as a GPU implementation manual for many numerical algorithms, sharing tips on GPUs that can increase application [...]

[...] readers as a starting point for adaptation in their applications. The book will serve as a GPU implementation manual for many numerical algorithms providing valuable insights into parallelization [...]

[...] leading to reusable, adaptable, and scalable code fragments. The book will serve as a GPU implementation manual for many image processing and analysis algorithms providing valuable insights into [...]

[...] course will teach how to write and optimize applications that fully leverage the multi-core processing capabilities of the GPU. Benefits include: Hands-on exercises and progressive lectures [...]

[...] course will teach you how to write applications in OpenCL that fully leverage the multi-core processing capabilities of the GPU. Taught by Acceleware developers who bring real world experience to the [...]

[...] day course teaches how to write and optimize applications that fully leverage the multi-core processing capabilities of the GPU. More details and registration: http://acceleware.com/training/986 [...]

[...] will teach you how to write and optimize applications that fully leverage the multi-core processing capabilities of the GPU. This course will have a finance focus. Commonly used algorithms such as [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU and GPU. In [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU and GPU. In the new 0.4.0 version, the library provides also a [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA and OpenCL) and Intel Xeon Phi. The new 0.6.0 [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA and OpenCL) and Intel Xeon Phi. The new 0.7.0 [...]

[...] PARALUTION is a library for sparse iterative methods which can be performed on various parallel devices, including multi-core CPU, GPU (CUDA and OpenCL) and Intel Xeon Phi. The new 0.8.0 [...]