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Probing biomolecular machines with graphics processors

James C. Phillips, John E. Stone

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Tags: Biology, Biomolecules, CUDA, GPU cluster, Molecular simulation, nVidia, OpenCL, Review, Tesla S1070

February 23, 2011 by hgpu

Efficient compilation of fine-grained SPMD-threaded programs for multicore CPUs

John A. Stratton, Vinod Grover, Jaydeep Marathe, Bastiaan Aarts, Mike Murphy, Ziang Hu, Wen-mei W. Hwu

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Tags: Algorithms, Computer science, CUDA, nVidia, OpenCL, Programming techniques

February 20, 2011 by hgpu

Decoupled Access/Execute Metaprogramming for GPU-Accelerated Systems

Lee Howes, Anton Lokhmotov, Paul H.J. Kelly, Alastair F. Donaldson

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Tags: CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX 280, OpenCL

February 19, 2011 by hgpu

High Performance Relevance Vector Machine on GPUs

Depeng Yang, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL

February 19, 2011 by hgpu

A Generic Approach for Developing Highly Scalable Particle-Mesh Codes for GPUs

W. Honig, F. Schmitt, R. Widera, H. Burau, G. Juckeland, M. S. Muller, and M. Bussmann

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Tags: ATI Radeon HD 5770, Computer science, CUDA, nVidia, OpenCL, Particle-in-cell methods, Plasma physics, Tesla C2050, Tesla S1070

February 19, 2011 by hgpu

Performance Comparison of Cholesky Decomposition on GPUs and FPGAs

Depeng Yang, Junqing Sun, JunKu Lee, Getao Liang, David D. Jenkins, Gregory D. Peterson, and Husheng Li

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Tags: Computer science, FPGA, Matrix decomposition, nVidia, nVidia GeForce GTX 480, OpenCL, Performance

February 18, 2011 by hgpu

OpenCL Evaluation for Numerical Linear Algebra Library Development

Peng Du, Piotr Luszczek, Jack Dongarra

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Tags: ATI Radeon HD 5870, Computer science, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla C2050

February 17, 2011 by hgpu

Static Memory Access Pattern Analysis on a Massively Parallel GPU

Byunghyun Jang, Dana Schaa, Perhaad Mistry, and David Kaeli

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Tags: Computer science, Matrix multiplication, Memory model, nVidia, nVidia GeForce 8800 Ultra, nVidia GeForce GTX 285, OpenCL, Optimization

February 16, 2011 by hgpu

An experimental study on performance portability of OpenCL kernels

Sean Rul, Hans Vandierendonck, Joris D'Haene and Koen De Bosschere

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Tags: ATI, ATI FirePro V8700, Cell processor, Computer science, nVidia, OpenCL, Performance, Playstation, Tesla C1060

February 16, 2011 by hgpu

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

K.A. Hawick, A. Leist, and D.P. Playne

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Tags: Cell processor, Computer science, CUDA, Data parallelism, Finite difference, nVidia, nVidia GeForce GTX 295, OpenCL, Partial differential equations, PDEs, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

Comparison of several parallel API for cloth modelling on modern GPUs

Tzvetomir Ivanov Vassilev

Tags: Computer science, CUDA, GLSL, nVidia, OpenCL, OpenGL, Performance

February 11, 2011 by hgpu

A New Data Layout For Set Intersection on GPUs

Rasmus Resen Amossen, Rasmus Pagh

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Tags: Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 285, OpenCL, PyOpenCL

February 7, 2011 by hgpu

FBLAS: BLAS implementation for Intel FPGA

FBLAS: Streaming Linear Algebra Kernels on FPGA

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

Titan: A CUDA-based physics simulation sandbox for high-performance robotics, physics, and reinforcement learning applications

Titan: A Parallel Asynchronous Library for Multi-Agent and Soft-Body Robotics using NVIDIA CUDA

onYourMarks: A deep learning benchmark implementation for Nvidia's Jetson TX2

Benchmarking Deep Learning Models on Jetson TX2

Hacking Neural Networks: A small course on exploiting and defending neural networks

Hacking Neural Networks: A Short Introduction

A Computing Kernel for Network Binarization on PyTorch

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

SHA512AOCLStudy

Study of OpenCL Processing Models for FPGA Devices

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

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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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