high performance computing on graphics processing units: hgpu.org

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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

A Push-Relabel-Based Maximum Cardinality Bipartite Matching Algorithm on GPUs

Mehmet Deveci, Kamer Kaya, Bora Ucar, Umit V. Catalyurek

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, Graph theory, nVidia, Search, Tesla C2050

January 5, 2014 by hgpu

Fast Parallel Image Registration on CPU and GPU for Diagnostic Classification of Alzheimer’s Disease

Denis P. Shamonin, Esther E. Bron, Boudewijn P. Lelieveldt, Marion Smits, Stefan Klein, Marius Staring

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Tags: Bioinformatics, Image processing, Image registration, Medicine, MRI, Neuroscience, nVidia, nVidia GeForce GTX 480, OpenCL

January 2, 2014 by hgpu

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

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Hristo Djidjev, Sunil Thulasidasan, Guillaume Chapuis, Rumen Andonov, Dominique Lavenier

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Tags: Algorithms, Bioinformatics, Biology, CUDA, GPU cluster, nVidia, Tesla C2090

December 18, 2013 by hgpu

Exploiting parallel features of modern computer architectures in bioinformatics

Guillaume Chapuis

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Genetics, nVidia, Path problems, Tesla C2050, Tesla C2090, Thesis

December 16, 2013 by hgpu

Graphics Processing Unit-Accelerated Quantitative Trait Loci Detection

Guillaume Chapuis, Olivier Filangi, Dominique Lavenier, Jean Michel J. M. Elsen, Pascale Leroy

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

November 16, 2013 by hgpu

Accelerating calculations of RNA secondary structure partition functions using GPUs

Harry A Stern, David H Mathews

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, RNA, Tesla M2050

November 11, 2013 by hgpu

High-performance Dynamic Programming on FPGAs with OpenCL

Sean O. Settle

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Tags: Bioinformatics, Computer science, FPGA, Heterogeneous systems, OpenCL, RNA, Smith-Waterman algorithm

October 29, 2013 by hgpu

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Darragh G McArt, Peter Bankhead, Philip D Dunne, Manuel Salto-Tellez, Peter Hamilton, Shu-Dong Zhang

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

October 17, 2013 by hgpu

High performance sequence mining using pairwise statistical significance

Yuhong Zhang, Feng Chen

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

October 12, 2013 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

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

A Push-Relabel-Based Maximum Cardinality Bipartite Matching Algorithm on GPUs

Fast Parallel Image Registration on CPU and GPU for Diagnostic Classification of Alzheimer’s Disease

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

Efficient Multi-GPU Computation of All-Pairs Shortest Paths

Exploiting parallel features of modern computer architectures in bioinformatics

Graphics Processing Unit-Accelerated Quantitative Trait Loci Detection

Accelerating calculations of RNA secondary structure partition functions using GPUs

High-performance Dynamic Programming on FPGAs with OpenCL

cudaMap: a GPU accelerated program for gene expression connectivity mapping

High performance sequence mining using pairwise statistical significance

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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