OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems
TLDR
The OpenCL standard offers a common API for program execution on systems composed of different types of computational devices such as multicore CPUs, GPUs, or other accelerators as mentioned in this paper, such as accelerators.Abstract:
The OpenCL standard offers a common API for program execution on systems composed of different types of computational devices such as multicore CPUs, GPUs, or other accelerators.read more
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Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges
TL;DR: This paper defines MCC, explains its major challenges, discusses heterogeneity in convergent computing and networking, and divides it into two dimensions, namely vertical and horizontal.
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Implementing molecular dynamics on hybrid high performance computers - short range forces
TL;DR: Algorithm for efficient short range force calculation on hybrid high-performance machines, an approach for dynamic load balancing of work between CPU and accelerator cores, and the Geryon library that allows a single code to compile with both CUDA and OpenCL for use on a variety of accelerators are described.
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Deep learning on image denoising: An overview.
TL;DR: A comparative study of deep techniques in image denoising by classifying the deep convolutional neural networks for additive white noisy images, the deep CNNs for real noisy images; the deepCNNs for blind Denoising and the deep network for hybrid noisy images.
Journal ArticleDOI
The fast azimuthal integration Python library: pyFAI .
Giannis Ashiotis,Aurore Deschildre,Zubair Nawaz,Jonathan P. Wright,Dimitrios Karkoulis,Frederic Picca,Jérôme Kieffer +6 more
TL;DR: This article details the geometry, peak-picking, calibration and integration procedures on multi- and many-core devices implemented in the Python library for high-performance azimuthal integration.
Journal ArticleDOI
A Survey of CPU-GPU Heterogeneous Computing Techniques
Sparsh Mittal,Jeffrey S. Vetter +1 more
TL;DR: This article surveys Heterogeneous Computing Techniques (HCTs) such as workload partitioning that enable utilizing both CPUs and GPUs to improve performance and/or energy efficiency and reviews both discrete and fused CPU-GPU systems.
References
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VMD: Visual molecular dynamics
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Scalable parallel programming with CUDA
TL;DR: Presents a collection of slides covering the following topics: CUDA parallel programming model; CUDA toolkit and libraries; performance optimization; and application development.
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Scalable Parallel Programming with CUDA: Is CUDA the parallel programming model that application developers have been waiting for?
TL;DR: In this article, the authors present a framework to develop mainstream application software that transparently scales its parallelism to leverage the increasing number of processor cores, much as 3D graphics applications transparently scale their parallelism on manycore GPUs with widely varying numbers of cores.
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Accelerating molecular modeling applications with graphics processors
John E. Stone,James C. Phillips,Peter L. Freddolino,David J. Hardy,Leonardo G. Trabuco,Klaus Schulten +5 more
TL;DR: An overview of recent advances in programmable GPUs is presented, with an emphasis on their application to molecular mechanics simulations and the programming techniques required to obtain optimal performance in these cases.