high performance computing on graphics processing units: hgpu.org

hgpu.org » Genetics

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

Kevin L. Keys, Gary K. Chen, Kenneth Lange

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Tags: Bioinformatics, Genetics, Machine learning, nVidia, OpenCL, Package, Statistics, Tesla C2050

August 8, 2016 by hgpu

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Kenichi W. Okamoto, Priyanga Amarasekare

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Tags: Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 690, Package

April 3, 2016 by hgpu

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

David S. Lawrie

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Tags: Algorithms, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 780 M, nVidia GeForce GTX 980

March 10, 2016 by hgpu

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

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Tags: Algorithms, Biology, CUDA, Genetics, Machine learning, Neuroscience, nVidia, nVidia GeForce GTX Titan, Statistics

September 9, 2014 by hgpu

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

Guillaume Chapuis

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

July 3, 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

Pairwise Sequence Alignment for Very Long Sequences on GPUs

J. Li, S. Ranka, S. Sahni

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Tags: CUDA, Genetics, nVidia, nVidia Tesla C2050, Sequence alignment, Smith-Waterman algorithm

April 2, 2014 by hgpu

Applying GPU Dynamic Parallelism to High-Performance Normalization of Gene Expressions

R.P. Souto, C. Osthoff, A.T.R. de Vasconcelos, D.A. Augusto, P.L. da Silva Dias, A. Rodriguez, O. Trelles, M. Ujaldon

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Tags: CUDA, Genetics, nVidia, Sorting, Tesla K20c

March 22, 2014 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

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

Sungin Park, Soo-Yong Shin, Kyu-Baek Hwang

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Tags: Bioinformatics, Biology, CUDA, Genetics, Multidimensional scaling, nVidia, Package

June 21, 2013 by hgpu

GPU based Eulerian Assembly of Genomes

Syed Faraz Mahmood

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia Quadro FX 5800, Thesis

March 7, 2013 by hgpu

Massive parallelization of combinatorial statistical genetics analyses porting machine learning methods on general purpose graphics processing units (GPU)

Tony Kam-Thong

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Tags: Biology, CUDA, Genetics, Machine learning, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, Package, Thesis

September 16, 2012 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Exploiting parallel features of modern computer architectures in bioinformatics: applications to genetics, structure comparison and large graph analysis

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

Pairwise Sequence Alignment for Very Long Sequences on GPUs

Applying GPU Dynamic Parallelism to High-Performance Normalization of Gene Expressions

Exploiting parallel features of modern computer architectures in bioinformatics

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

GPU based Eulerian Assembly of Genomes

Massive parallelization of combinatorial statistical genetics analyses porting machine learning methods on general purpose graphics processing units (GPU)

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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