high performance computing on graphics processing units: hgpu.org

Siegfried Benkner, Sabri Pllana, Jesper Larsson Traff, Philippas Tsigas, Uwe Dolinsky, Cedric Augonnet, Beverly Bachmayer, Christoph Kessler, David Moloney, Vitaly Osipov

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Tags: Code generation, Computer science, Heterogeneous systems, Hybrid computing, nVidia, OpenCL, Tesla C1060

October 20, 2011 by hgpu

FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm

P. Hanappe, A. Beurive, F. Laguzet, L. Steels, N. Bellouin, O. Boucher, Y. H. Yamazaki, T. Aina, M. Allen

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Tags: Algorithms, Cell processor, Earth and Space Sciences, Fortran, nVidia, nVidia GeForce GT 330 M, OpenCL, Weather prediction, Weather Prediction Model

October 20, 2011 by hgpu

Explicit platform descriptions for heterogeneous many-core architectures

Martin Sandrieser, Siegfried Benkner and Sabri Pllana

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Tags: Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL

October 20, 2011 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control

Accelerating exotic option pricing and model calibration using GPUs

OpenMP for Accelerators

Efficient Synchronization Primitives for GPUs

Automatic program analysis for data parallel kernels

GPU Accelerated X-Ray Image Enhancement

Enabling Computational Dynamics in Distributed Computing Environments Using a Heterogeneous Computing Template

A high performance computing framework for physics-based modeling and simulation of military ground vehicles

Experimental B+-tree for GPU

PEPPHER: Efficient and Productive Usage of Hybrid Computing Systems

FAMOUS, faster: using parallel computing techniques to accelerate the FAMOUS/HadCM3 climate model with a focus on the radiative transfer algorithm

Explicit platform descriptions for heterogeneous many-core architectures

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)