high performance computing on graphics processing units: hgpu.org

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A new gravitational N-body simulation algorithm for investigation of cosmological chaotic advection

Diego H. Stalder, Reinaldo R. Rosa, Jose da Silve Junior, Esteban Clua, Renata Ruiz, Haroldo F. Campos Velho, Fernando Ramos, Amarisio da Silva Araujo, Vitor Gomes Conrado

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Tags: Astrophysics, Cosmology, Cosmology and Extragalactic Astrophysics, CUDA, Gravitation, N-body simulation, nVidia, nVidia GeForce GTX 680

August 17, 2012 by hgpu

Data Partitioning on Heterogeneous Multicore and Multi-GPU Systems Using Functional Performance Models of Data-Parallel Applications

Ziming Zhong, Vladimir Rychkov, Alexey Lastovetsky

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 680, Tesla C870

July 12, 2012 by hgpu

Using visualization to reveal weak cryptosystems

Eirik Eggesbo Ottesen

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Tags: Computer science, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 570, nVidia GeForce GTX 680, Security, Thesis, Visualization

June 5, 2012 by hgpu

Tuning a Finite Difference Computation for Parallel Vector Processors

Gerhard Zumbusch

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Tags: Algorithms, Computer science, Finite difference, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Performance

May 24, 2012 by hgpu

An Efficient Work-Distribution Strategy for Gridding Radio-Telescope Data on GPUs

John W. Romein

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Tags: Astrophysics, ATI, ATI Radeon HD 7970, CUDA, nVidia, nVidia GeForce GTX 680, OpenCL, Performance

April 25, 2012 by hgpu

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

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high performance computing on graphics processing units: hgpu.org

A new gravitational N-body simulation algorithm for investigation of cosmological chaotic advection

Data Partitioning on Heterogeneous Multicore and Multi-GPU Systems Using Functional Performance Models of Data-Parallel Applications

Using visualization to reveal weak cryptosystems

Tuning a Finite Difference Computation for Parallel Vector Processors

An Efficient Work-Distribution Strategy for Gridding Radio-Telescope Data on GPUs

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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