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eccCL: parallelized GPU implementation of Ensemble Classifier Chains

Mona Riemenschneider, Alexander Herbst, Ari Rasch, Sergei Gorlatch, Dominik Heider

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Tags: Biology, Computer science, Java, Next-Generation sequencing, nVidia, OpenCL, Package, R, Tesla K20

August 26, 2017 by hgpu

Simulating the Cardinal Movements of Childbirth Using Finite Element Analysis on the Graphics Processing Unit

Zelimkhan Gerikhanov

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Tags: AMD Radeon HD 8970 M, ATI, Biology, Biomechanics, FEM, Finite element method, Medicine, MRI, OpenCL, Thesis

August 17, 2017 by hgpu

Gpufit: An open-source toolkit for GPU-accelerated curve fitting

Adrian Przybylski, Bjorn Thiel, Jan Keller-Findeisen, Bernd Stock, Mark Bates

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Tags: Biology, Computer science, CUDA, Microscopy, nVidia, nVidia GeForce GTX 1080, Package, Python

August 17, 2017 by hgpu

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

Data-Parallel Flattening by Expansion

Data-Parallel Flattening by Expansion

IA-SpGEMM: An Input-aware Auto-tuning Framework for Parallel Sparse Matrix-Matrix Multiplication

IA-SpGEMM: An Input-aware Auto-tuning Framework for Parallel Sparse Matrix-Matrix Multiplication

MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization

MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization

TensorNetwork: A library for easy and efficient manipulation of tensor networks

TensorNetwork for Machine Learning

triSYCL: Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group

SYCL Code Generation for Multigrid Methods

PSST: A Tutorial for Parallelised Scalable Simulations in TensorFlow

Parallel scalable simulations of biological neural networks using TensorFlow: A beginner’s guide

MUSE: Miami University Simulation Environment

Temporospatial Epidemic Simulations Using Heterogeneous Computing

Pressure Point Analysis framework

Diagnosing Performance Bottlenecks in HPC Applications

Dynamic Distribution Pruning for Efficient Network Architecture Search

Dynamic Distribution Pruning for Efficient Network Architecture Search

Tinker-HP: High Performance Massively Parallel Evolution of Tinker

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

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2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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