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Toward OpenCL Automatic Multi-Device Support

Henry Sylvain, Alexandre Denis, Denis Barthou, Marie-Christine Counilh, Raymond Namyst

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Tesla M2075

June 15, 2014 by hgpu

Enabling CP2K Application for Exascale Computing with Accelerators using OpenACC and OpenCL

Mariusz Uchronski, Agnieszka Kwiecien, Marcin Gebarowski

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Tags: ATI, ATI Radeon HD 6950, Chemistry, CUDA, Matrix multiplication, Molecular simulation, MPI, nVidia, OpenACC, OpenCL, Sparse matrix, Tesla M2075

May 16, 2014 by hgpu

Code Optimization and Performance Analysis of Oceanographic Software Package NEMO for GPGPU Systems

Plamenka Borovska, Desislava Ivanova

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Tags: CUDA, Earth and Space Sciences, Heterogeneous systems, nVidia, Tesla M2075

May 12, 2014 by hgpu

Dynamic Instrumentation and Optimization for GPU Applications

Naila Farooqui, Christopher J. Rossbach, Yuan Yu

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques, Tesla M2075

April 16, 2014 by hgpu

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

Luka Stanisic, Samuel Thibault, Arnaud Legrand, Brice Videau, Jean-Francois Mehaut

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Performance, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075

April 9, 2014 by hgpu

An efficient GPU acceptance-rejection algorithm for the selection of the next reaction to occur for Stochastic Simulation Algorithms

Neri Mickael, Denis Mestivier

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Tags: Algorithms, Biology, Computer science, CUDA, nVidia, Optimization, Stochastic simulation, Tesla K10, Tesla K20, Tesla M2075, Tesla M2090

April 4, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 by hgpu

Fast American Basket Option Pricing on a multi-GPU Cluster

Michael Benguigui, Francoise Baude

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Tags: Finance, GPU cluster, Machine learning, nVidia, OpenCL, Option pricing, Tesla M2050, Tesla M2075, Tesla S1070

February 17, 2014 by hgpu

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Vivek K. Pallipuram

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Performance, Tesla K20, Tesla M2075, Thesis

February 11, 2014 by hgpu

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Naoya Maruyama, Takayuki Aoki

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Source codes

Tags: Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla K20, Tesla M2075

January 26, 2014 by hgpu

Job Parallelism using Graphical Processing Unit Individual Multi-Processors and Localised Memory

D.P. Playne, K.A. Hawick

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Tags: Computer science, CUDA, Data parallelism, nVidia, Tesla M2075

December 11, 2013 by hgpu

Highly Optimized Full GPU-Acceleration of Non-hydrostatic Weather Model SCALE-LES

Mohamed Wahib, Naoya Maruyama

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Tags: CUDA, Earth and Space Sciences, nVidia, OpenACC, Tesla K20, Tesla M2075, Weather Prediction Model

November 29, 2013 by wahibium

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Toward OpenCL Automatic Multi-Device Support

Enabling CP2K Application for Exascale Computing with Accelerators using OpenACC and OpenCL

Code Optimization and Performance Analysis of Oceanographic Software Package NEMO for GPGPU Systems

Dynamic Instrumentation and Optimization for GPU Applications

Modeling and Simulation of a Dynamic Task-Based Runtime System for Heterogeneous Multi-Core Architectures

An efficient GPU acceptance-rejection algorithm for the selection of the next reaction to occur for Stochastic Simulation Algorithms

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

Fast American Basket Option Pricing on a multi-GPU Cluster

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Job Parallelism using Graphical Processing Unit Individual Multi-Processors and Localised Memory

Highly Optimized Full GPU-Acceleration of Non-hydrostatic Weather Model SCALE-LES

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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