Results 61 to 70 of about 15,151 (210)
Fast acceleration of 2D wave propagation simulations using modern computational accelerators. [PDF]
PLoS ONE, 2014 Recent developments in modern computational accelerators like Graphics Processing Units (GPUs) and coprocessors provide great opportunities for making scientific applications run faster than ever before.
Wei Wang +4 more
doaj +1 more source
Pydidas: a tool for automated X‐ray diffraction data analysis
Journal of Applied Crystallography, Volume 58, Issue 4, Page 1476-1485, August 2025.Pydidas is a new Python package for processing X‐ray diffraction data, offering a user‐friendly interface and versatile processing options. It includes a graphical user interface for the entire data processing pipeline and is intended to be easily accessible for non‐experts.The processing and analysis of X‐ray diffraction (XRD) data at synchrotrons is ...
Malte Storm +2 more
wiley +1 more source
Leveraging SYCL for Heterogeneous cDTW Computation on CPU, GPU, and FPGA
Concurrency and Computation: Practice and Experience, Volume 37, Issue 15-17, 25 July 2025.ABSTRACT One of the most time‐consuming kernels of a recent epileptic seizure detection application is the computation of the constrained Dynamic Time Warping (cDTW) Distance Matrix. In this paper, we explore the design space of heterogeneous CPU, GPU, and FPGA implementations of this kernel using SYCL as a programming model. First, we optimize the CPU
Cristian Campos +3 more
wiley +1 more source
The IMAGE beamline at the KIT Light Source
Journal of Synchrotron Radiation, Volume 32, Issue 4, Page 1036-1051, July 2025.The superconducting wiggler beamline IMAGE at the KIT Light Source, dedicated to full‐field hard X‐ray imaging applications in materials and life sciences, with a focus on high‐throughput computed tomography, laminography experiments and systematic in situ and operando studies, is described.The superconducting wiggler beamline IMAGE at the KIT Light ...
Angelica Cecilia +14 more
wiley +1 more source
Stencil Computations on AMD and Nvidia Graphics Processors: Performance and Tuning Strategies
Concurrency and Computation: Practice and Experience, Volume 37, Issue 12-14, 25 June 2025.ABSTRACT Over the last ten years, graphics processors have become the de facto accelerator for data‐parallel tasks in various branches of high‐performance computing, including machine learning and computational sciences. However, with the recent introduction of AMD‐manufactured graphics processors to the world's fastest supercomputers, tuning ...
Johannes Pekkilä +3 more
wiley +1 more source
Challenges of the Knowledge Society, 2012 Since the first idea of using GPU to general purpose computing, things have evolved over the years and now there are several approaches to GPU programming. GPU computing practically began with the introduction of CUDA (Compute Unified Device Architecture)
BOGDAN OANCEA +2 more
doaj
International Journal of Reconfigurable Computing, 2019 Solving diagonally dominant tridiagonal linear systems is a common problem in scientific high-performance computing (HPC). Furthermore, it is becoming more commonplace for HPC platforms to utilise a heterogeneous combination of computing devices.
Hamish J. Macintosh +2 more
doaj +1 more source
CUDA and OpenCL implementations of Conways Game of Life cellular automata [PDF]
Компьютерные исследования и моделирование, 2010 In this article the experience of reading "CUDA and OpenCL programming" course during high perfomance computing summer school MIPT-2010 is analyzed. Content of lectures and practical tasks, as well as manner of presenting of the material are regarded ...
Andrey Evgen'evich Alekseenko +1 more
doaj +1 more source
Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures
, 2018 For reasons of both performance and energy efficiency, high-performance computing (HPC) hardware is becoming increasingly heterogeneous. The OpenCL framework supports portable programming across a wide range of computing devices and is gaining influence ...
Johnston, Beau, Milthorpe, Josh
core +1 more source
InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA
Software: Practice and Experience, Volume 55, Issue 6, Page 1127-1141, June 2025.ABSTRACT Introduction Unity is a powerful and versatile tool for creating real‐time experiments. It includes a built‐in compute shader language, a C‐like programming language designed for massively parallel General‐Purpose GPU (GPGPU) computing. However, as Unity is primarily developed for multi‐platform game creation, its compute shader language has ...
David Algis +3 more
wiley +1 more source