high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Biology

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus

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Tags: Bioinformatics, Biology, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sequence alignment, Smith-Waterman algorithm

February 27, 2015 by azhar ali

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Edgardo Mejia-Roa, Daniel Tabas-Madrid, Javier Setoain, Carlos Garcia, Francisco Tirado, Alberto Pascual-Montano

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Factorization, GPU cluster, MPI, Nonnegative matrix factorization, nVidia, Package, Tesla C1060

February 19, 2015 by hgpu

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

Matija Korpar, Martin Sosic, Dino Blazeka, Mile Sikic

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Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX 780, Package, Smith-Waterman algorithm

January 16, 2015 by hgpu

Bayesian neural networks for detecting epistasis in genetic association studies

Andrew L Beam, Alison Motsinger-Reif, Jon Doyle

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Tags: Bayesian, Biology, CUDA, CULA, Neural networks, nVidia, Package, Python

December 15, 2014 by hgpu

MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

Dinghua Li, Chi-Man Liu, Ruibang Luo, Kunihiko Sadakane, Tak-Wah Lam

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Tags: Biology, CUDA, Genomics, nVidia, Package, Tesla K40

September 29, 2014 by hgpu

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Gary K. Chen, Eric Chi, John Ranola, Kenneth Lange

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Tags: Algorithms, Bioinformatics, Biology, Cluster analysis, Clustering, Genomics, Hierarchical clustering, nVidia, OpenCL, Package, Tesla C2050

September 9, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

An efficient parallel algorithm for accelerating computational protein design

Yichao Zhou, Wei Xu, Bruce R. Donald, Jianyang Zeng

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Java, nVidia, Package, Tesla K20

June 23, 2014 by hgpu

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

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

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 480, Package, Python, Sequence alignment, Tesla K10, Tesla K20

May 25, 2014 by hgpu

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

Shuang Wang, Jihoon Kim, Xiaoqian Jiang, Stefan F Brunner, Lucila Ohno-Machado

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, RNA, Smith-Waterman algorithm, Tesla M2090

May 10, 2014 by hgpu

Bayesian Neural Networks for Genetic Association Studies of Complex Disease

Andrew L. Beam, Alison Motsinger-Reif, Jon Doyle

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Tags: Bayesian, Biology, CUDA, Machine learning, Neural networks, nVidia, Package, Python

April 17, 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

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Packages

Implementation of Smith-Waterman algorithm in OpenCL for GPUs

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

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

Bayesian neural networks for detecting epistasis in genetic association studies

MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph

Convex Clustering: An Attractive Alternative to Hierarchical Clustering

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

An efficient parallel algorithm for accelerating computational protein design

GPU-BSM: A GPU-Based Tool to Map Bisulfite-Treated Reads

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda

Bayesian Neural Networks for Genetic Association Studies of Complex Disease

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

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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