high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Biology

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

View

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

View

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

View

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

View

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

View

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

View

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

View

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

July 26, 2016 by hgpu

Accelerated cryo-EM structure determination with parallelisation using GPUs in relion-2

Dari Kimanius, Bjorn O Forsberg, Sjors HW Scheres, Erik Lindahl

View

Tags: Biology, Cryo-EM, CUDA, Image processing, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980 Ti

July 5, 2016 by hgpu

PROJECTION Algorithm for Motif Finding on GPUs

Jhoirene B. Clemente, Francis George C. Cabarle, Henry N. Adorna

View

Tags: Algorithms, Biology, Computational biology, CUDA, nVidia

May 26, 2016 by hgpu

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

Kenichi W. Okamoto, Priyanga Amarasekare

View

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

April 3, 2016 by hgpu

A Massively Parallel Algorithm for Cell Classification Using CUDA

Samuel Schmidt

View

Tags: Bioinformatics, Biology, CUDA, Machine learning, nVidia, nVidia GeForce GTX 770, RNA, Thesis

March 20, 2016 by hgpu

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

David S. Lawrie

View

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

March 10, 2016 by hgpu

hls4ml: A package for machine learning inference in FPGAs

Fast convolutional neural networks on FPGAs with hls4ml

Adaptive Partial STEM

Advances in Electron Microscopy with Deep Learning

Linus: easy-to-share, interactive 3D figures

linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser

Compound Word Transformer

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

SAPFOR

Interactive Parallelization of C Programs in SAPFOR

CUDA Memtrace

Exploiting BSP Abstractions for Compiler Based Optimizations of GPU Applications on multi-GPU Systems

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

waLBerla: (widely applicable Lattice Boltzmann from Erlangen), massively parallel framework for multi physics applications

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Systolic CNN

Systolic-CNN: An OpenCL-defined Scalable Run-time-flexible FPGA Accelerator Architecture for Accelerating Convolutional Neural Network Inference in Cloud/Edge Computing

See all packages

* * *

* * *

2021

April

27-29

Munich, Germany

9th International Workshop on OpenCL and SYCL, 2021

2020

December

10-14

Virtually in Barcelona, Spain

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

2020

November

24-27

Naha, Okinawa, Japan

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2021

January

13-15

Shenzhen, China

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

2020

December

14-16

Bangkok, Thailand

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020

+

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: