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An exploration of CUDA and CBEA for a gravitational wave source-modelling application

Gaurav Khanna, Justin McKennon

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Tags: Cell processor, CUDA, General Relativity and Quantum Cosmology, Gravitation, nVidia, Physics, Tesla C1060

November 9, 2010 by hgpu

Teraflop per second gravitational lensing ray-shooting using graphics processing units

Alexander C. Thompson, Christopher J. Fluke, David G. Barnes, Benjamin R. Barsdell

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Gravitational lensing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 GT, Tesla S1070

November 9, 2010 by hgpu

High Performance Direct Gravitational N-body Simulations on Graphics Processing Units: An implementation in CUDA (thesis)

Jeroen Bedorf

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Tags: Astrophysics, CUDA, Gravitation, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Package, Stellar dynamics

November 9, 2010 by hgpu

Running the NIM Next-Generation Weather Model on GPUs

Mark W. Govett, Jacques Middlecoff, Tom Henderson

Tags: CUDA, Earth and Space Sciences, nVidia, Weather Prediction Model

November 9, 2010 by hgpu

Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit

Wangda Zuo, Qingyan Chen

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Tags: CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce 8800 GTX

November 9, 2010 by hgpu

Gravitational tree-code on graphics processing units: implementation in CUDA

Evghenii Gaburov, Jeroen Bedorf, Simon P. Zwart

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 Ultra, Package, Physics

November 9, 2010 by hgpu

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

A. Zhmurov, K. Rybnikov, Y. Kholodov, V. Barsegov

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Tags: Biological Physics, Chemical Physics, CUDA, nVidia, nVidia GeForce GTX 295, Physics, Pseudo-random number generators

November 9, 2010 by hgpu

Massively parallel differential evolution-pattern search optimization with graphics hardware acceleration: an investigation on bound constrained optimization problems

Weihang Zhu

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Tags: Computer science, CUDA, Differential evolution, Finance, nVidia, nVidia GeForce GTX 280, Pattern Search

November 9, 2010 by hgpu

ABC-SysBio–approximate Bayesian computation in Python with GPU support

Juliane Liepe, Chris Barnes, Erika Cule, Kamil Erguler, Paul Kirk, Tina Toni, Michael P. H. Stumpf

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Python

November 9, 2010 by hgpu

DiVinE-CUDA – A Tool for GPU Accelerated LTL Model Checking

Jiri Barnat, Lubos Brim, Milan Ceska

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia GeForce GTX 280, Software Engineering

November 9, 2010 by hgpu

Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

Kimikazu Kato, Tikara Hosino

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Tags: Computer science, CUDA, Data Structures and Algorithms, Information Retrieval, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 280

November 8, 2010 by hgpu

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Anthony Lee, Christopher Yau, Michael B. Giles, Arnaud Doucet, Christopher C. Holmes

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Tags: CUDA, Mathematics, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Statistics

November 8, 2010 by hgpu

sycl-bench: SYCL Benchmark Suite

SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing

BlaBla: A Python package for clinical linguistic feature extraction in multiple languages

BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages

gocudnn: Go Bindings for cudnn and other cuda pacakges

Deep Learning with GO

Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

Task-Based Parallel Strategies for CFD Application in Heterogeneous CPU/GPU Resources

DALI: a library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

Importance of Data Loading Pipeline in Training Deep Neural Networks

AutoParBench: a benchmark framework to evaluate compilers and tools designed to automatically insert OpenMP directives

AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

cuda-kat: The CUDA Kernel Author's Toolkit

cuda-kat: The CUDA Kernel Author’s Toolkit

HPCC FPGA: A OpenCL-based FPGA benchmark suite for HPC

Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite

GEVO: GPU Code Optimization using Evolutionary Computation

GEVO: GPU Code Optimization using Evolutionary Computation

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

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

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