high performance computing on graphics processing units: hgpu.org

Trevor Bekolay, James Bergstra, Eric Hunsberger, Travis DeWolf, Terrence C. Stewart, Daniel Rasmussen, Xuan Choo, Aaron Russell Voelker, Chris Eliasmith

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Tags: ATI, ATI Radeon HD 7970, Biology, Neuroscience, nVidia, nVidia GeForce GTX 280, OpenCL, Package, PyOpenCL, Python

January 9, 2014 by hgpu

Multicore Computing: Algorithms, Architectures, and Applications

Sanguthevar Rajasekaran, Lance Fiondella, Mohamed Ahmed, Reda A. Ammar

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Tags: Algorithms, Biology, Book, Computer science, CUDA, Linear Algebra, nVidia, String matching, Tesla

January 6, 2014 by hgpu

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

Pinghao Li, Xiaoqian Jiang, Shuang Wang, Jihoon Kim, Hongkai Xiong, Lucila Ohno-Machado

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Tags: Algorithms, Bioinformatics, Biology, Clustering, Compression, CUDA, nVidia, Package, Sequence alignment, Tesla M2090

December 27, 2013 by hgpu

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

H. Khaled, R. El Gohary, N. L. Badr, H. M. Faheem

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 540 M, Sequence alignment, Smith-Waterman algorithm

December 22, 2013 by hgpu

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Hristo Djidjev, Sunil Thulasidasan, Guillaume Chapuis, Rumen Andonov, Dominique Lavenier

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Tags: Algorithms, Bioinformatics, Biology, CUDA, GPU cluster, nVidia, Tesla C2090

December 18, 2013 by hgpu

triSYCL: Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group

SYCL Code Generation for Multigrid Methods

Dynamic Distribution Pruning for Efficient Network Architecture Search

Tinker-HP: High Performance Massively Parallel Evolution of Tinker

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

PyVisc

Classify QCD phase transition with deep learning

Bytespresso: a library for Java to C/CUDA translator based on deep reification

A Development Platform for Embedded Domain-Specific Languages

faimGraph

Breadth-First Search using Dynamic Parallelism on the GPU

Vulkan Multi-GPU application

Multi-GPU Rendering with Vulkan API

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high performance computing on graphics processing units: hgpu.org

Applications

A Multi GPU Read Alignment Algorithm with Model-based Performance Optimization

MICA: A fast short-read aligner that takes full advantage of Intel Many Integrated Core Architecture (MIC)

Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

GPU-Accelerated BWT Construction for Large Collection of Short Reads

Accelerating a Bayesian Phylogenetic Inference Application with OpenACC

Optimal Alignment of Three Sequences On A GPU

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

Nengo: a Python tool for building large-scale functional brain models

Multicore Computing: Algorithms, Architectures, and Applications

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Recent source codes

triSYCL: Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group

PSST: A Tutorial for Parallelised Scalable Simulations in TensorFlow

MUSE: Miami University Simulation Environment

Pressure Point Analysis framework

Dynamic Distribution Pruning for Efficient Network Architecture Search

Tinker-HP: High Performance Massively Parallel Evolution of Tinker

PyVisc

Bytespresso: a library for Java to C/CUDA translator based on deep reification

faimGraph

Vulkan Multi-GPU application

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Featured events

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019