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Fast Radix Sort for Sparse Linear Algebra on GPU

Lukas Polok, Viorela Ila, Pavel Smrz

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780, OpenCL, Sorting, Sparse matrix

March 18, 2015 by hgpu

RadixBoost: A Hardware Acceleration Structure for Scalable Radix Sort on Graphic Processors

Xingyu Liu, Shikai Li, Kuan Fang, Yufei Ni, Zonghui Li, Yangdong Deng

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Tags: Algorithms, ASIC, Computer science, FPGA, nVidia, nVidia GeForce GTX 580, Sorting

March 12, 2015 by hgpu

Very Fast Non-Dominated Sorting

Czeslaw Smutnicki, Jaroslaw Rudy, Dominik Zelazny

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, Sorting, Tesla K20

February 24, 2015 by hgpu

Hybrid Multicore Algorithms for Some Semi-Numerical Applications and Graphs

Dip Sankar Banerjee

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Tags: Algorithms, Cell processor, Computer science, CUDA, Distributed computing, List ranking, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, OpenCL, Sorting, Thesis

January 19, 2015 by hgpu

Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units

Amlan Chatterjee

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Sorting, Tesla K20, Thesis

January 16, 2015 by hgpu

A Novel Computational Model for GPUs with Applications to Efficient Algorithms

Atsushi Koike, Kunihiko Sadakane

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Tags: Algorithms, Computer science, CUDA, nVidia, Sorting, Tesla C1060, Tesla K20

January 15, 2015 by hgpu

Real-Time Incompressible Fluid Simulation on the GPU

Xiao Nie, Leiting Chen, Tao Xiang

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Tags: 3D Graphics and Realism, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 780, Real-time graphics, Sorting

January 2, 2015 by hgpu

GPU Declarative Framework

Robert W. Senser, Jr.

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Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

Runtime Comparison of CPU and GPU Using Portable Programming Models

Franz Wiesinger, Florian Nairz, Michael Bogner

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 680, OpenCL, Sorting

November 29, 2014 by hgpu

A Performance Comparison of Sort and Scan Libraries for GPUs

Bruce Merry

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Tags: Algorithms, AMD Radeon R9 270, ATI, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting, Tesla K40

October 20, 2014 by hgpu

Improved GPU Co-processor Sorting Algorithm with Barrier Synchronization

K. Avinash, Monu Pandey, Ajinkya Deshpande, M. Rajasekhara Babu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Sorting

August 13, 2014 by hgpu

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 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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