high performance computing on graphics processing units: hgpu.org

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Clacc: Translating OpenACC to OpenMP in Clang

Joel E. Denny, Seyong Lee, Jeffrey S. Vetter

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Tags: Compilers, Computer science, Heterogeneous systems, LLVM, nVidia, nVidia GeForce GTX 1050, OpenACC, OpenMP

December 9, 2018 by hgpu

High Performance Portable Tsunami Simulations on Many-core CPU, GPU, and FPGA

Fumiya Kono

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Tags: AMD FirePro W8100, AMD FirePro W9100, AMD Radeon R9 280X, ATI, CUDA, Earth and Space Sciences, FPGA, Intel Xeon Phi, Numerical simulation, nVidia, OpenCL, Tesla K20, Thesis

December 9, 2018 by hgpu

ASW: Accelerating Smith-Waterman Algorithm on Coupled CPU-GPU Architecture

Huihui Zou, Shanjiang Tang, Ce Yu, Hao Fu, Yusen Li, Wenjie Tang

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Tags: Algorithms, APU, Bioinformatics, Biology, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 750, OpenCL, Sequence alignment, Smith-Waterman algorithm

December 9, 2018 by hgpu

Optimization of a discontinuous finite element solver with OpenCL and StarPU

Philippe Helluy, Laura Mendoza, Bruno Weber

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Tags: Algorithms, Computer science, Hybrid computing, nVidia, nVidia GeForce GTX 1050 Ti, nVidia Quadro P 6000, OpenCL, Package, Task scheduling

December 9, 2018 by hgpu

A Framework for Fast and Efficient Neural Network Compression

Hyeji Kim, Muhammad Umar Karim, Chong-Min Kyung

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Tags: ARM, Caffe, Compression, Computational Complexity, Computer science, Computer vision, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti

December 9, 2018 by hgpu

A Fast and Simple Approach to Merge and Merge Sort using Wide Vector Instructions

Alex Watkins, Oded Green

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Tags: Algorithms, Computer science, Intel Xeon Phi, Sorting

December 2, 2018 by hgpu

Mix-and-Match: A Model-driven Runtime Optimisation Strategy for BFS on GPUs

Merijn Verstraaten, Ana Lucia Varbanescu, Cees de Laat

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Tags: Breadth-First Search, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package

December 2, 2018 by hgpu

Parallel source code transformation techniques using design patterns

David del Rio Astorga

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Tags: Algorithms, Auto-Tuning, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Tesla K40, Thesis

December 2, 2018 by hgpu

PanJoin: A Partition-based Adaptive Stream Join

Fei Pan, Hans-Arno Jacobsen

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Tags: Algorithms, Computer science, Databases, FPGA, OpenCL

December 2, 2018 by hgpu

Performance Portability Challenges for Fortran Applications

Abigail Hsu, David Neill Asanza, Joseph A. Schoonover, Zach Jibben, Neil N. Carlson, Robert Robey

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Tags: Computer science, CUDA, Finite difference, Fortran, nVidia, OpenMP, Package, performance portability, Tesla P100, Tesla V100

December 2, 2018 by hgpu

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks

Linnan Wang, Wei Wu, Yiyang Zhao, Junyu Zhang, Hang Liu, George Bosilca, Jack Dongarra, Maurice Herlihy, Rodrigo Fonseca

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Tags: Compression, Computer science, CUDA, Deep learning, FFT, GPU cluster, Neural networks, nVidia, Package, Tesla P100

November 25, 2018 by hgpu

CLort: High Throughput and Low Energy Network Intrusion Detection on IoT Devices with Embedded GPUs

Charalampos Stylianopoulos, Linus Johansson, Oskar Olsson, Magnus Almgren

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Tags: ARM, Computer science, IoT, OpenCL, Package, Security

November 25, 2018 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

Clacc: Translating OpenACC to OpenMP in Clang

High Performance Portable Tsunami Simulations on Many-core CPU, GPU, and FPGA

ASW: Accelerating Smith-Waterman Algorithm on Coupled CPU-GPU Architecture

Optimization of a discontinuous finite element solver with OpenCL and StarPU

A Framework for Fast and Efficient Neural Network Compression

A Fast and Simple Approach to Merge and Merge Sort using Wide Vector Instructions

Mix-and-Match: A Model-driven Runtime Optimisation Strategy for BFS on GPUs

Parallel source code transformation techniques using design patterns

PanJoin: A Partition-based Adaptive Stream Join

Performance Portability Challenges for Fortran Applications

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks

CLort: High Throughput and Low Energy Network Intrusion Detection on IoT Devices with Embedded GPUs

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Most viewed papers (last 30 days)