high performance computing on graphics processing units: hgpu.org

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Power analysis of sorting algorithms on FPGA using OpenCL

Aidan O Mahony, Emanuel Popovici

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Tags: Computer science, Energy-efficient computing, FPGA, OpenCL, Performance, Sorting

November 3, 2018 by hgpu

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

Ricardo Nobre, Luis Reis, Joao M. P. Cardoso

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Tags: Computer science, nVidia, nVidia GeForce GTX 1070, OpenCL, Performance, PTX

October 28, 2018 by hgpu

A study of integer sorting on multicores

Alexandros V. Gerbessiotis

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Tags: Algorithms, Computer science, MPI, Package, Performance, Sorting

September 2, 2018 by hgpu

Performance Evaluation of OpenMP’s Target Construct on GPUs – Exploring Compiler Optimizations

Akihiro Hayashi, Jun Shirako, Etorre Tiotto, Robert Ho, Vivek Sarkar

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Tags: Compilers, Computer science, CUDA, LLVM, nVidia, OpenMP, Performance, Tesla K80, Tesla P100

August 26, 2018 by hgpu

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke

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Tags: Computer science, Deep learning, Intel Xeon Phi, OpenMP, Package, Performance

August 19, 2018 by hgpu

A Cross-platform Evaluation of Graphics Shader Compiler Optimization

Lewis Crawford, Michael O'Boyle

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Tags: 3D Graphics and Realism, Computer science, Optimization, Performance, Real-time graphics, Shaders, Virtual reality, Vulkan

August 11, 2018 by hgpu

Elementary functions: towards automatically generated, efficient, and vectorizable implementations

Hugues De Lassus Saint-Genies

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Tags: Algorithms, Code generation, Computer science, Elementary functions, Performance, Thesis

July 28, 2018 by hgpu

Block-Size Independence for GPU Programs

Rajeev Alur, Joseph Devietti, Nimit Singhania

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, Performance

July 28, 2018 by hgpu

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Simon Garcia De Gonzalo, Wen-Mei Hwu, Simon D. Hammond, Christian R. Trott

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Tags: Computer science, Intel Xeon Phi, nVidia, Performance, Sparse matrix, Tesla P100

July 15, 2018 by hgpu

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Ben Karsin, Volker Weichert, Henri Casanova, John Iacono, Nodari Sitchinava

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 770, nVidia Quadro M 4000, Performance, Sorting, Tesla K40

July 1, 2018 by hgpu

Improving tasks throughput on accelerators using OpenCL command concurrency

A.J. Lazaro-Munoz, J.M. Gonzalez-Linares, J. Gomez-Luna, N. Guil

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Tags: AMD Radeon R9, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Task scheduling, Tesla K20

June 28, 2018 by hgpu

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

Shizhao Chen, Jianbin Fang, Donglin Chen, Chuanfu Xu, Zheng Wang

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Tags: Computer science, Intel Xeon Phi, Machine learning, OpenMP, Performance, Sparse matrix

June 9, 2018 by hgpu

PAstudy

Double-precision FPUs in High-Performance Computing: an Embarrassment of Riches?

hpx: The C++ Standard Library for Parallelism and Concurrency

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms, i.e., dwarfs, for state-of-art multicore CPUs, GPUs, Intel MICs and Altera FPGAs

OpenCL Performance Prediction using Architecture-Independent Features

Rodinia Benchmark Suite ported for OpenCL-capable Intel FPGAs

High Performance Computing with FPGAs and OpenCL

The Ocean Tensor Package

Tornado

Using Compiler Snippets to Exploit Parallelism on Heterogeneous Hardware: A Java Reduction Case Study

pocl: Portable Computing Language

Exploiting Task Parallelism with OpenCL: A Case Study

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

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high performance computing on graphics processing units: hgpu.org

Power analysis of sorting algorithms on FPGA using OpenCL

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

A study of integer sorting on multicores

Performance Evaluation of OpenMP’s Target Construct on GPUs – Exploring Compiler Optimizations

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

A Cross-platform Evaluation of Graphics Shader Compiler Optimization

Elementary functions: towards automatically generated, efficient, and vectorizable implementations

Block-Size Independence for GPU Programs

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Improving tasks throughput on accelerators using OpenCL command concurrency

Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures

Recent source codes

PAstudy

hpx: The C++ Standard Library for Parallelism and Concurrency

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms, i.e., dwarfs, for state-of-art multicore CPUs, GPUs, Intel MICs and Altera FPGAs

Rodinia Benchmark Suite ported for OpenCL-capable Intel FPGAs

The Ocean Tensor Package

Tornado

pocl: Portable Computing Language

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

Most viewed papers (last 30 days)

Featured events

International Conference on Image, Video and Signal Processing (IVSP), 2019

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018