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New Efficient Method To Solve Longest Overlap Region Problem For Noncoding DNA Sequence

Yukun Zhong, ZhiWei He, XianHong Wang, Liao Gang

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 610 M

April 16, 2014 by hgpu

A Way For Accelerating The DNA Sequence Reconstruction Problem By CUDA

Yukun Zhong, ZhiWei He, XianHong Wang, XiongBin Cao

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 610 M, Sorting

April 16, 2014 by hgpu

MaxSSmap: A GPU program for short read mapping with the maximum scoring subsequence

Usman Roshan

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Tags: Bioinformatics, Biology, CUDA, nVidia, Short read mapping, Smith-Waterman algorithm, Tesla M2050

March 12, 2014 by hgpu

Parallelization of DNA alignment algorithms using GPUs

Gustavo Encarnacao

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 580, Sequence matching, Suffix trees

March 7, 2014 by hgpu

Hybrid Framework for 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: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 540 M, Sequence alignment, Smith-Waterman algorithm

March 6, 2014 by hgpu

QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

Adam Gudys, Sebastian Deorowicz

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Tags: ATI, ATI Radeon HD 7970, Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Package, Sequence alignment

March 4, 2014 by hgpu

A Multi GPU Read Alignment Algorithm with Model-based Performance Optimization

Aleksandr Drozd, Naoya Maruyama, Satoshi Matsuoka

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla C2050

March 1, 2014 by hgpu

MICA: A fast short-read aligner that takes full advantage of Intel Many Integrated Core Architecture (MIC)

Sze-Hang Chan, Jeanno Cheung, Edward Wu, Heng Wang, Chi-Man Liu, Xiaoqian Zhu, Shaoliang Peng, Ruibang Luo, Tak-Wah Lam

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Tags: Bioinformatics, Biology, Intel Xeon Phi, Package

February 21, 2014 by hgpu

Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

Dariusz Mrozek, Milosz Brozek, Bozena Malysiak-Mrozek

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 560 Ti, Package, Tesla C1060

February 4, 2014 by hgpu

Accelerating a Bayesian Phylogenetic Inference Application with OpenACC

Joao Pedro de Matos Neves

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Tags: Bayesian, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 580, OpenACC

January 25, 2014 by hgpu

Optimal Alignment of Three Sequences On A GPU

Junjie Li, Sanjay Ranka, Sartaj Sahni

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla C2050

January 14, 2014 by hgpu

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

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

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 480, Package, Smith-Waterman algorithm, Tesla K20

January 12, 2014 by hgpu

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

See all packages

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high performance computing on graphics processing units: hgpu.org

New Efficient Method To Solve Longest Overlap Region Problem For Noncoding DNA Sequence

A Way For Accelerating The DNA Sequence Reconstruction Problem By CUDA

MaxSSmap: A GPU program for short read mapping with the maximum scoring subsequence

Parallelization of DNA alignment algorithms using GPUs

Hybrid Framework for pairwise DNA Sequence Alignment Using the CUDA compatible GPU

QuickProbs – A Fast Multiple Sequence Alignment Algorithm Designed for Graphics Processors

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

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

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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