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

Efficient Interleaved Batch Matrix Solvers for CUDA

ArborX: Performance-portable geometric search library

ArborX: A Performance Portable Search Library

FlowSeq: Generative Flow based Sequence-to-Sequence Toolkit

FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

Compositional Deep Learning in Futhark

MLPerf Benchmark Suite

Demystifying the MLPerf Benchmark Suite

stdgpu: Efficient STL-like Data Structures on the GPU

ikra-cpp: C++ Library for Object-oriented Programming with Structure of Arrays Layout

Memory-Efficient Object-Oriented Programming on GPUs

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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

Watershed analysis algorithm implementation in CUDA and OpenACC

OpenCL Performance Prediction using Architecture-Independent Features

PySPH: a Python-based SPH framework

Efficient Interleaved Batch Matrix Solvers for CUDA

ArborX: Performance-portable geometric search library

FlowSeq: Generative Flow based Sequence-to-Sequence Toolkit

Compositional Deep Learning in Futhark

MLPerf Benchmark Suite

stdgpu: Efficient STL-like Data Structures on the GPU

ikra-cpp: C++ Library for Object-oriented Programming with Structure of Arrays Layout

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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