high performance computing on graphics processing units: hgpu.org

Luigi Nardi, Bruno Bodin, M. Zeeshan Zia, John Mawer, Andy Nisbet, Paul H. J. Kelly, Andrew J. Davison, Mikel Lujan, Michael F. P. O'Boyle, Graham Riley, Nigel Topham, Steve Furber

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Tags: Algorithms, ARM, Benchmarking, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance

October 10, 2014 by hgpu

FDTD on Distributed Heterogeneous Multi-GPU Systems

Eirik Myklebost

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Tags: Algorithms, Benchmarking, Cluster computing, CUDA, Electrodynamics, FDTD, Finite-difference time-domain, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 470, nVidia GeForce GTX 760, Physics, Tesla K20, Thesis, Ultrasound

October 10, 2014 by hgpu

NAS Parallel Benchmarks for GPGPUs using a Directive-based Programming Model

Rengan Xu, Xiaonan Tian, Sunita Chandrasekaran, Yonghong Yan, Barbara Chapman

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, OpenACC, Tesla K20

September 28, 2014 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

See all packages

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high performance computing on graphics processing units: hgpu.org

CHO: A Benchmark Suite for OpenCL-based FPGA Accelerators

GPU: Power vs Performance

Performance comparison of Lattice Boltzmann fluid flow simulation using OpenCL and CUDA frameworks

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Automatic Tuning of Local Memory Use on GPGPUs

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Scalable Verification Techniques for Data-Parallel Programs

A Performance Comparison of Sort and Scan Libraries for GPUs

Leo: A Profile-Driven Dynamic Optimization Framework for GPU Applications

Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM

FDTD on Distributed Heterogeneous Multi-GPU Systems

NAS Parallel Benchmarks for GPGPUs using a Directive-based Programming Model

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

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