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Harnessing the power of idle GPUs for acceleration of biological sequence alignment

Fumihiko Ino, Yuki Kotani, Yuma Munekawa, Kenichi Hagihara

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce 7900 GTX, nVidia GeForce 7950 GX2, nVidia GeForce 8800 GTX, OpenGL, Sequence alignment

July 12, 2011 by hgpu

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

T. Bonny, M.A. Zidan, K.N. Salama

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia Quadro FX 4800, Sequence alignment, Smith-Waterman algorithm

July 7, 2011 by hgpu

Striped Smith-Waterman speeds database searches six times over other SIMD implementations

M. Farrar

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Tags: Algorithms, Bioinformatics, Biology, Sequence alignment, Smith-Waterman algorithm

July 6, 2011 by hgpu

Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors

Torbjorn Rognes, Erling Seeberg

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Tags: Algorithms, Bioinformatics, Biology, Sequence alignment, Smith-Waterman algorithm

July 6, 2011 by hgpu

Graphics processing unit implementations of relative expression analysis algorithms enable dramatic computational speedup

Andrew T. Magis, John C. Earls, Youn-Hee H. Ko, James A. Eddy, Nathan D. Price

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Package

July 1, 2011 by hgpu

CAMPAIGN: An open-source Library of GPU-accelerated Data Clustering Algorithms

Kai J. Kohlhoff, Marc H. Sosnick, William T. Hsu, Vijay S. Pande, Russ B. Altman

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Tags: Bioinformatics, Biology, Clustering, CUDA, nVidia, Package

July 1, 2011 by hgpu

Accelerating Smith-Waterman Local Sequence Alignment on GPU Cluster

Thuy T. Nguyen, Duc H. Nguyen, Phong H. Pham, Ngoc M. Ta, Tan N. Duong, Hung D. Le

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Tags: Bioinformatics, Biology, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GTX 295, Sequence alignment, Smith-Waterman algorithm, Tesla C1060

June 27, 2011 by hgpu

Accelerating Smith-Waterman on Heterogeneous CPU-GPU Systems

Jaideep Singh, Ipseeta Aruni

Tags: Bioinformatics, Biology, CUDA, Heterogeneous systems, nVidia, Smith-Waterman algorithm

June 24, 2011 by hgpu

Protein alignment algorithms with an efficient backtracking routine on multiple GPUs

Jacek Blazewicz, Wojciech Frohmberg, Michal Kierzynka, Erwin Pesch, Pawel Wojciechowski

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Package, Sequence alignment, Tesla S1070

June 21, 2011 by hgpu

Accelerating Genome-Wide Association Studies Using CUDA Compatible Graphics Processing Units

Rui Jiang, Feng Zeng, Wangshu Zhang, Xuebing Wu, Zhihong Yu

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 280

June 15, 2011 by hgpu

The accelerating implementation of BLAST with stream processor

Gang Wei, Chao Ma, Songwen Pei, Baifeng Wu

Tags: ATI, ATI Radeon HD 4850, Bioinformatics, Biology, BLAST, Brook, Sequence alignment

June 15, 2011 by hgpu

The scoring sequences on profile Hidden Markov Models with delete states elimination by GPUs

Jun Li, Yanhui Li, Shuangping Chen

Tags: Bioinformatics, Computer science, nVidia, nVidia GeForce 9800 GTX, Sequence alignment

June 10, 2011 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Harnessing the power of idle GPUs for acceleration of biological sequence alignment

An Adaptive Hybrid Multiprocessor technique for bioinformatics sequence alignment

Striped Smith-Waterman speeds database searches six times over other SIMD implementations

Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors

Graphics processing unit implementations of relative expression analysis algorithms enable dramatic computational speedup

CAMPAIGN: An open-source Library of GPU-accelerated Data Clustering Algorithms

Accelerating Smith-Waterman Local Sequence Alignment on GPU Cluster

Accelerating Smith-Waterman on Heterogeneous CPU-GPU Systems

Protein alignment algorithms with an efficient backtracking routine on multiple GPUs

Accelerating Genome-Wide Association Studies Using CUDA Compatible Graphics Processing Units

The accelerating implementation of BLAST with stream processor

The scoring sequences on profile Hidden Markov Models with delete states elimination by GPUs

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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