high performance computing on graphics processing units: hgpu.org

hgpu.org » Sequence alignment

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

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

Matthias Alexander Lee

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Tags: Bioinformatics, Biology, Computational Complexity, CUDA, nVidia, Package, Python, RNA, Sequence alignment, Signal processing

May 31, 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

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 570, nVidia GeForce GTX 690, Package, Sequence alignment, Smith-Waterman algorithm

April 23, 2013 by hgpu

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

Parallel Implementation of Dynamic Programming Algorithm Using Graphics Processing Unit

M. Khurram Rehman, M. Umer Sarwar, M. Ramzan Talib, M. Salman Mansoor, M. Bilal Sarwar

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Tags: Algorithms, Bioinformatics, Biology, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GT 525 M, nVidia GeForce GT 610 M, Sequence alignment

April 6, 2013 by hgpu

GPU-Based Cloud Service for Smith-Waterman algorithm Using Frequency Distance Filtration Scheme

Sheng-Ta Lee, Chun-Yuan Lin, Che Lun Hung

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Tags: Bioinformatics, Biology, Cloud, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C2050

March 18, 2013 by hgpu

Binary Interval Search: a scalable algorithm for counting interval intersections

Ryan M. Layer, Kevin Skadron, Gabriel Robins, Ira M. Hall, Aaron R. Quinlan

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Tags: Algorithms, Bioinformatics, Biology, Computer science, CUDA, Monte Carlo simulation, nVidia, Package, Sequence alignment

February 6, 2013 by hgpu

Burrows-Wheeler Aligner: A Parallel Approach

Sheridan Lee Wright

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Tags: Algorithms, Bioinformatics, Biology, CUDA, MPI, nVidia, Sequence alignment, Thesis

January 16, 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

GPU Acceleration of Pyrosequencing Noise Removal

Yang Gao, Jason D. Bakos

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Tags: Algorithms, Bioinformatics, Biology, Clustering, CUDA, MPI, nVidia, Sequence alignment, Tesla C2070

November 10, 2012 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

GPU Multiple Sequence Alignment Fourier-Space Cross-Correlation Alignment

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

SW# – GPU enabled exact alignments on genome scale

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Parallel Implementation of Dynamic Programming Algorithm Using Graphics Processing Unit

Binary Interval Search: a scalable algorithm for counting interval intersections

Burrows-Wheeler Aligner: A Parallel Approach

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

GPU Acceleration of Pyrosequencing Noise Removal

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Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

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