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

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

SHA512AOCLStudy

Study of OpenCL Processing Models for FPGA Devices

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

JSDoop

JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training

FPGA CNN Acceleration

Research on OpenCL optimization for FPGA deep learning application

PyTorchPipe: a framework for rapid prototyping of pipelines combining language and vision

Performance Evaluation of Advanced Features in CUDA Unified Memory

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

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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

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

SHA512AOCLStudy

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

JSDoop

FPGA CNN Acceleration

PyTorchPipe: a framework for rapid prototyping of pipelines combining language and vision

Performance Evaluation of Advanced Features in CUDA Unified Memory

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

Most viewed papers (last 30 days)

Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

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