high performance computing on graphics processing units: hgpu.org

Ruibang Luo, Thomas Wong, Jianqiao Zhu, Chi-Man Liu, Edward Wu, Lap-Kei Lee, Haoxiang Lin, Wenjuan Zhu, David W. Cheung, Hing-Fung Ting, Siu-Ming Yiu, Chang Yu, Yingrui Li, Ruiqiang Li, Tak-Wah Lam

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Package, Tesla C2070, Tesla M2050

February 25, 2013 by hgpu

G-SNPM – A GPU-based SNP mapping tool

Alessandro Orro, Andrea Manconi, Emanuele Manca, Giuliano Armano, Luciano Milanesi

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, nVidia GeForce GTX 480, Package, Python, Smith-Waterman algorithm

November 14, 2012 by hgpu

GHOSTM: A GPU-Accelerated Homology Search Tool for Metagenomics

Shuji Suzuki, Takashi Ishida, Ken Kurokawa, Yutaka Akiyama

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Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, Package, Tesla S1070

May 10, 2012 by hgpu

Exact and complete short-read alignment to microbial genomes using Graphics Processing Unit programming

Jochen Blom, Tobias Jakobi, Daniel Doppmeier, Sebastian Jaenicke, Jorn Kalinowski, Jens Stoye, Alexander Goesmann

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, Package

May 10, 2011 by hgpu

Exact and complete short read alignment to microbial genomes using GPU programming

Jochen Blom, Tobias Jakobi, Daniel Doppmeier, Sebastian Jaenicke, Jorn Kalinowski, Jens Stoye, Alexander Goesmann

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Tags: Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, nVidia GeForce GTX 280, Package

April 11, 2011 by hgpu

DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

Yongchao Liu, Bertil Schmidt, Douglas Maskell

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Tags: Bioinformatics, Biology, CUDA, MPI, Next-Generation sequencing, nVidia, OpenMP, Package, Tesla S1070

April 11, 2011 by hgpu

GPU-RMAP: Accelerating Short-Read Mapping on Graphics Processors

Ashwin M. Aji, Liqing Zhang, Wu C. Feng

Tags: Bioinformatics, Biology, Next-Generation sequencing, nVidia

March 9, 2011 by hgpu

clRNG: an OpenCL based software library containing random number generation functions

A tool set for random number generation on GPUs in R

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Faster-Mean-Shift-Euc

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Turbo: A constraint solver purely on GPUs (CUDA)

A Variant of Concurrent Constraint Programming on GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

eccCL: parallelized GPU implementation of Ensemble Classifier Chains

Parallelization, Scalability, and Reproducibility in Next-Generation Sequencing Analysis

SW#db: GPU-accelerated exact sequence similarity database search

GPU-accelerated Computation for Statistical Analysis of the Next-Generation Sequencing Data

cuBLASTP: Fine-Grained Parallelization of Protein Sequence Search on a GPU

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

G-SNPM – A GPU-based SNP mapping tool

GHOSTM: A GPU-Accelerated Homology Search Tool for Metagenomics

Exact and complete short-read alignment to microbial genomes using Graphics Processing Unit programming

Exact and complete short read alignment to microbial genomes using GPU programming

DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

GPU-RMAP: Accelerating Short-Read Mapping on Graphics Processors

Recent source codes

clRNG: an OpenCL based software library containing random number generation functions

DLRM: An implementation of a deep learning recommendation model

OpenMM: A High Performance Molecular Dynamics Library

Fancier High-Performance API

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

Faster-Mean-Shift-Euc

Turbo: A constraint solver purely on GPUs (CUDA)

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