high performance computing on graphics processing units: hgpu.org

hgpu.org » CUDA

GPU-based ultrafast IMRT plan optimization

Chunhua Men,Xuejun Gu,Dongju Choi,Amitava Majumdar,Ziyi Zheng,Klaus Mueller,Steve B. Jiang

View

Tags: CUDA, Medicine, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 285, Tesla C1060, Tesla C1070

October 27, 2010 by hgpu

GPU Based Acceleration of Telegraph Equation

Vaclav Simek, Michal Kraus, Kunovsky Jiri, Jiri Petrek

View

Tags: Algorithms, Computer science, CUDA, nVidia

October 27, 2010 by hgpu

Importance of Explicit Vectorization for CPU and GPU Software Performance

Neil G. Dickson, Kamran Karimi, Firas Hamze

View

Tags: Computer science, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, Physics

October 27, 2010 by hgpu

GPU sample sort

Nikolaj Leischner, Vitaly Osipov, Peter Sanders

View

Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 285, Sorting, Tesla C1060

October 27, 2010 by hgpu

PyTorch: An Imperative Style, High-Performance Deep Learning Library

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Masivo: Parallel public transport routes simulation

Masivo: Parallel Simulation Model Based on OpenCL for Massive Public Transportation Systems’ Routes

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

See all packages

* * *

* * *

* * *

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

+

HGPU group © 2010-2019 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: