high performance computing on graphics processing units: hgpu.org

Applications

Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis

Jesus Perez Serrano, Edans Flavius De Oliveira Sandes, Alba Cristina Magalhaes Alves de Melo, Manuel Ujaldon

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Tags: Bioinformatics, Biology, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 980, Performance, Smith-Waterman algorithm

June 10, 2017 by hgpu

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Weihua Guo, You Xu, Xueyang Feng

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Tags: Biology, Computer science, Deep learning, Medicine, nVidia, nVidia GeForce GTX 1080, Package, Python, TensorFlow

May 11, 2017 by hgpu

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Pascal Libuschewski

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Tags: Biology, Computer vision, Design space exploration, Microscopy, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 560 Ti, nVidia Quadro NVS 3100 M, OpenCL, Thesis, Visualization

April 20, 2017 by hgpu

A Domain Specific Language for Performance Portable Molecular Dynamics Algorithms

William R. Saunders, James Grant, Eike H. Muller

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Tags: Algorithms, Biology, Chemistry, Code generation, Computer science, CUDA, Differential equations, DSL, Molecular dynamics, nVidia, Package, Partial differential equations, PDEs, Physics, Python, Tesla K20

April 15, 2017 by hgpu

Exploiting Multi-level Parallelism on a Many-core System for the Application of Hyperheuristics to a Molecular Docking Problem

Jose M. Cecilia, Jose-Matias, Cutillas-Lozano, Domingo Gimenez, Baldomero Imbernon

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Tags: Bioinformatics, Biology, Chemistry, Intel Xeon Phi, Metaheuristics, molecular docking

March 20, 2017 by hgpu

First Experiences Optimizing Smith-Waterman on Intel’s Knights Landing Processor

Enzo Rucci, Carlos Garcia, Guillermo Botella, Armando De Giusti, Marcelo Naiouf, Manuel Prieto-Matias

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Tags: Bioinformatics, Biology, Computer science, Intel Xeon Phi, Sequence alignment, Smith-Waterman algorithm

February 26, 2017 by hgpu

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

Felipe Sulser Larraz

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Tags: Benchmarking, Bioinformatics, Biology, Computer science, Databases, Filtering, Intel Xeon Phi, Sequence alignment, Smith-Waterman algorithm, Thesis

February 2, 2017 by hgpu

Using efficient parallelization in Graphic Processing Units to parameterize stochastic fire propagation models

Monica Denham, Karina Laneri, Juan Manuel Morales

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Tags: Biology, CUDA, Earth and Space Sciences, nVidia, nVidia GeForce GTX 780, nVidia GeForce GTX Titan, Package, Tesla C2070, Tesla K40

January 16, 2017 by hgpu

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

Pilar Cossio, David Rohr, Fabio Baruffa, Markus Rampp, Volker Lindenstruth, Gerhard Hummer

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Tags: Bayesian, Biology, Biomolecules, CUDA, Electron microscopy, Heterogeneous systems, Medicine, Microscopy, MPI, nVidia, nVidia GeForce GTX Titan, OpenMP, Package, Tesla K20, Tomography

October 8, 2016 by hgpu

Parallel Tree Traversal for Nearest Neighbor Query on the GPU

Moohyeon Nam, Jinwoong Kim, Beomseok Nam

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Tags: Algorithms, Biology, Computational biology, Computer science, CUDA, Information Retrieval, Nearest neighbour, nVidia, Tesla K40

September 5, 2016 by hgpu

Drug Drug Interaction Extraction from Biomedical Literature Using Syntax Convolutional Neural Network

Zhehuan Zhao, Zhihao Yang, Ling Luo, Hongfei Lin, Jian Wang

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Tags: Bioinformatics, Biology, CUDA, Deep learning, Neural networks, NLP, nVidia, Package, Python, Tesla K20, Text mining

August 1, 2016 by hgpu

Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support

Marius Erbert, Steffen Rechner, Matthias Muller-Hannemann

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan, Package

July 26, 2016 by hgpu

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Snowflake: A Lightweight Portable Stencil DSL

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

OpenAdSCL

Scalar collapse in AdS with an OpenCL open source code

Rgtsvm: Support Vector Machines on a GPU in R

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high performance computing on graphics processing units: hgpu.org

Applications

Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis

DeepMetabolism: A Deep Learning System to Predict Phenotype from Genome Sequencing

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

A Domain Specific Language for Performance Portable Molecular Dynamics Algorithms

Exploiting Multi-level Parallelism on a Many-core System for the Application of Hyperheuristics to a Molecular Docking Problem

First Experiences Optimizing Smith-Waterman on Intel’s Knights Landing Processor

Analysis and implementation of a BLAST-Like algorithm for MIC architectures

Using efficient parallelization in Graphic Processing Units to parameterize stochastic fire propagation models

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

Parallel Tree Traversal for Nearest Neighbor Query on the GPU

Drug Drug Interaction Extraction from Biomedical Literature Using Syntax Convolutional Neural Network

Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support

Recent source codes

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entropy-sgd: Lua implementation of Entropy-SGD

LightGBM-GPU: GPU Accelerated LightGBM for Histogram-based GBDT Training

Snowflake: A Lightweight Portable Stencil DSL

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

OpenAdSCL

Rgtsvm: Support Vector Machines on a GPU in R

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International Conference on Intelligent Autonomous Systems (ICIAS), 2018

International Conference on Robotics and Intelligent System (ICRIS), 2018

International Conference on Image and Graphics Processing (ICIGP), 2018

8th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB), 2018

The 10th International Conference on Computer Modeling and Simulation (ICCMS), 2018