high performance computing on graphics processing units: hgpu.org

Programming

The ANTAREX Domain Specific Language for High Performance Computing

Cristina Silvano, Giovanni Agosta, Andrea Bartolini, Andrea R. Beccari, Luca Benini, Loïc Besnard, João Bispo, Radim Cmar, João M. P. Cardoso, Carlo Cavazzoni, Daniele Cesarini, Stefano Cherubin, Federico Ficarelli, Davide Gadioli, Martin Golasowski, Antonio Libri, Jan Martinovič, Gianluca Palermo, Pedro Pinto, Erven Rohou, Kateřina Slaninová, Emanuele Vitali

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Tags: Auto-Tuning, Compilers, Computer science, DSL, OpenCL, Package

March 24, 2019 by hgpu

Accelerating ternary quantized convolutional neural networks using OpenCL for FPGA

Victor Joos de ter Beerst, Antoine Vanderschueren

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Tags: Computer science, DSP, FPGA, Neural networks, OpenCL, Package, Thesis

March 24, 2019 by hgpu

Novel Data-Partitioning Algorithms for Performance and Energy Optimization of Data-Parallel Applications on Modern Heterogeneous HPC Platforms

Hamidreza Khaleghzadeh

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Matrix multiplication, nVidia, OpenCL, Package, Thesis

March 17, 2019 by hgpu

CLTestCheck: Measuring Test Effectiveness for GPU Kernels

Chao Peng, Ajitha Rajan

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Tags: Computer science, OpenCL, Package, Performance

March 17, 2019 by hgpu

Performance Optimization of Memory Intensive Applications on FPGA Accelerator

Arslan Arif

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Tags: Artificial intelligence, Computer science, Electronic design automation, FPGA, nVidia, nVidia GeForce GTX 960, OpenCL, Thesis

March 17, 2019 by hgpu

Improving GPU Performance through Instruction Redistribution and Diversification

Xiang Gong

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Tags: AMD Radeon HD 7970, ATI, Compilers, Computer science, OpenCL, Optimization, Thesis

March 10, 2019 by hgpu

Energy Efficient Parallel K-Means Clustering for an Intel Hybrid Multi-Chip Package

Matheus Souza, Lucas Maciel, Pedro Henrique Penna, Henrique Freitas

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Tags: Clustering, Computer science, Energy-efficient computing, FPGA, Intel Xeon Phi, Machine learning, OpenCL

March 10, 2019 by hgpu

On the Portability of GPU-Accelerated Applications via Automated Source-to-Source Translation

Paul Sathre, Mark Gardner, Wu-chun Feng

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Tags: AMD FirePro S9150, ATI, Computer science, CUDA, FPGA, Intel Xeon Phi, nVidia, OpenCL, Package, performance portability, Tesla K80

March 10, 2019 by hgpu

Cooperative CPU, GPU, and FPGA heterogeneous execution with EngineCL

Maria Angelica Davila Guzman, Raul Nozal, Ruben Gran Tejero, Maria Villarroya-Gaudo, Dario Suarez Gracia, Jose Luis Bosque

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Tags: Computer science, FPGA, Heterogeneous systems, load balancing, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package

March 3, 2019 by hgpu

Application level energy measurements and models for hybrid platform with accelerators

Kenneth O'Brien

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, OpenCL, Tesla K40, Thesis

March 3, 2019 by hgpu

Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs

Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler

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Tags: Computer science, CUDA, FPGA, nVidia, OpenCL, Optimization, Performance, Tesla P100

March 3, 2019 by hgpu

An Empirically Guided Optimization Framework for FPGA OpenCL

Ahmed Sanaullah, Rushi Patel, Martin C. Herbordt

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Tags: Computer science, FPGA, OpenCL, Optimization

February 24, 2019 by hgpu

jax-md: Differentiable, Hardware Accelerated, Molecular Dynamics

JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python

libmolgrid: Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows

libmolgrid: GPU Accelerated Molecular Gridding for Deep Learning Applications

Single-Assignment C Base

Array Languages Make Neural Networks Fast

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

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

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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

Boston, MA, USA

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

2019

May

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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high performance computing on graphics processing units: hgpu.org

Programming

The ANTAREX Domain Specific Language for High Performance Computing

Accelerating ternary quantized convolutional neural networks using OpenCL for FPGA

Novel Data-Partitioning Algorithms for Performance and Energy Optimization of Data-Parallel Applications on Modern Heterogeneous HPC Platforms

CLTestCheck: Measuring Test Effectiveness for GPU Kernels

Performance Optimization of Memory Intensive Applications on FPGA Accelerator

Improving GPU Performance through Instruction Redistribution and Diversification

Energy Efficient Parallel K-Means Clustering for an Intel Hybrid Multi-Chip Package

On the Portability of GPU-Accelerated Applications via Automated Source-to-Source Translation

Cooperative CPU, GPU, and FPGA heterogeneous execution with EngineCL

Application level energy measurements and models for hybrid platform with accelerators

Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs

An Empirically Guided Optimization Framework for FPGA OpenCL

Recent source codes

jax-md: Differentiable, Hardware Accelerated, Molecular Dynamics

libmolgrid: Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows

Single-Assignment C Base

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

Masivo: Parallel public transport routes simulation

FBLAS: BLAS implementation for Intel FPGA

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

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

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

Most viewed papers (last 30 days)

Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

7th International Workshop on OpenCL, 2019

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

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

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