high performance computing on graphics processing units: hgpu.org

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Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

Sampath Kumar, P. K. Baruah

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Tags: Algorithms, Biology, Computational biology, CUDA, Databases, nVidia, Sequence matching, Smith-Waterman algorithm, Tesla M2050

November 2, 2013 by hgpu

A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets

Da Li, Kittisak Sajjapongse, Huan Truong, Gavin Conant, Michela Becchi

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Tags: Bioinformatics, Biology, Computational biology, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia Quadro FX 2000, Sequence alignment, Tesla K20

May 11, 2013 by hgpu

Streaming Data from HDD to GPUs for Sustained Peak Performance

Lucas Beyer, Paolo Bientinesi

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Tags: Biology, Computational biology, CUDA, nVidia, nVidia Quadro FX 6000, Tesla S2050

February 20, 2013 by hgpu

High performance bioinformatics and computational biology on general-purpose graphics processing units

Cheng Ling

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Tags: Bioinformatics, Biology, Computational biology, CUDA, FPGA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 460, Sequence alignment, Thesis

January 3, 2013 by hgpu

Parallel-META: efficient metagenomic data analysis based on high-performance computation

Xiaoquan Su, Jian Xu, Kang Ning

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Tags: Biology, Computational biology, CUDA, nVidia, Package, Tesla C2070

July 22, 2012 by hgpu

A Performance Model for Memory Bandwidth Constrained Applications on Graphics Engines

Lin Ma, Roger D. Chamberlain

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Tags: Biology, BLAST, Computational biology, CUDA, Hashing, nVidia, nVidia GeForce GTX 480, Performance

July 15, 2012 by hgpu

Parallel Implementation of the Wu-Manber Algorithm Using the OpenCL Framework

Themistoklis K. Pyrgiotis, Charalampos S. Kouzinopoulos, Konstantinos G. Margaritis

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Tags: Algorithms, Biology, Computational biology, Databases, nVidia, nVidia GeForce GTX 280, OpenCL, Pattern Search, Sequence matching

June 20, 2012 by hgpu

GPUmotif: An Ultra-Fast and Energy-Efficient Motif Analysis Program Using Graphics Processing Units

Pooya Zandevakili, Ming Hu, Zhaohui Qin

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Tags: Algorithms, Biochemistry, Biology, Chemistry, Computational biology, Computer science, CUDA, Genetics, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package

June 17, 2012 by hgpu

Range query processing in a multi-GPU environment

Ricardo J. Barrientos, Jose I. Gomez, Christian Tenllado, Manuel Prieto Matias, Mauricio Marin

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Tags: Algorithms, Biology, Computational biology, Computer science, CUDA, Databases, GPU cluster, nVidia, OpenMP, Tesla C1060

June 11, 2012 by hgpu

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

Haixiang Shi, Bertil Schmidt, Weiguo Liu, Wolfgang Muller-Wittig

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Tags: Algorithms, Biology, Computational biology, CUDA, Image processing, Machine learning, nVidia, Package, Tesla C2050

January 13, 2012 by hgpu

MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

Peng Jia, Liming Xuan, Lei Liu, Chaochun Wei

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Tags: Biology, Computational biology, CUDA, Genetics, nVidia, Package, Tesla C1060

January 11, 2012 by hgpu

kNN Query Processing in Metric Spaces Using GPUs

Ricardo J. Barrientos, Jose I. Gomez, Christian Tenllado, Manuel Prieto Matias, Mauricio Marin

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Tags: Algorithms, Biology, Computational biology, CUDA, Databases, Information Retrieval, nVidia, nVidia GeForce GTX 280

December 4, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Communication Optimization for Multi GPU Implementation of Smith-Waterman Algorithm

A Distributed CPU-GPU Framework for Pairwise Alignments on Large-Scale Sequence Datasets

Streaming Data from HDD to GPUs for Sustained Peak Performance

High performance bioinformatics and computational biology on general-purpose graphics processing units

Parallel-META: efficient metagenomic data analysis based on high-performance computation

A Performance Model for Memory Bandwidth Constrained Applications on Graphics Engines

Parallel Implementation of the Wu-Manber Algorithm Using the OpenCL Framework

GPUmotif: An Ultra-Fast and Energy-Efficient Motif Analysis Program Using Graphics Processing Units

Range query processing in a multi-GPU environment

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

kNN Query Processing in Metric Spaces Using GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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