high performance computing on graphics processing units: hgpu.org

hgpu.org » Pseudo-random number generators

ShoveRand: a model-driven framework to easily generate random numbers on GP-GPU

Jonathan Passerat-Palmbach, Claude Mazel, David R.C. Hill

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Tags: Computer science, CUDA, nVidia, Pseudo-random number generators, Stochastic simulation, Tesla C1060

November 19, 2011 by hgpu

Parallel Random Numbers: As Easy as 1, 2, 3

John K. Salmon, Mark A. Moraes, Ron O. Dror, and David E. Shaw

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Source codes

Tags: AES, ATI, ATI Radeon HD 6970, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Pseudo-random number generators, Security

October 28, 2011 by hgpu

A Hybrid Software Framework for the GPU Acceleration of Multi-Threaded Monte Carlo Applications

Joo Hong Lee, Mark T. Jones, Paul E. Plassmann

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Tags: ATI, ATI Radeon HD 5750, Computer science, Monte Carlo simulation, OpenCL, Pseudo-random number generators

October 24, 2011 by hgpu

An FPGA-specific algorithm for direct generation of multi-variate Gaussian random numbers

David B. Thomas, Wayne Luk

Tags: Algorithms, Computer science, CUDA, DSP, FPGA, Numerical simulation, nVidia, Pseudo-random number generators

August 30, 2011 by hgpu

A Variant of Mersenne Twister Suitable for Graphic Processors

Mutsuo Saito

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GT 120, nVidia GeForce GTX 260, Package, Pseudo-random number generators

August 3, 2011 by hgpu

High-Performance Pseudo-Random Number Generation on Graphics Processing Units

Nimalan Nandapalan, Richard P. Brent, Lawrence M. Murray, Alistair Rendell

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Tags: Algorithms, Computer science, CUDA, Number Theory, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Pseudo-random number generators

August 3, 2011 by hgpu

Pseudo-Random Number Generation on GP-GPU

Jonathan Passerat-Palmbach, Claude Mazel, David R. C. Hill

Tags: Algorithms, Computer science, Pseudo-random number generators

July 11, 2011 by hgpu

Pseudo-random number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices

Carolyn L. Phillips, Joshua A. Anderson, Sharon C. Glotzer

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Tags: Algorithms, Computer science, Package, Physics, Pseudo-random number generators

July 6, 2011 by hgpu

Hybrid Embarrassingly Parallel on heterogeneous platform

Chunye Gong, Jie Liu, Jin Qin, Qingfeng Hu, Zhenghu Gong

Tags: Benchmarking, Computer science, Heterogeneous systems, Pseudo-random number generators

June 8, 2011 by hgpu

Fast, Processor-Cardinality Agnostic PRNG with a Tracking Application

Andrew Janowczyk, Sharat Chandran, Srinivas Aluru

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, Particle filtering, Pseudo-random number generators

June 7, 2011 by hgpu

Efficient Embarrassingly Parallel on Graphics Processor Unit

Chunye Gong, Jie Liu, Jin Qin, Qingfeng Hu, Zhenghu Gong

Tags: Benchmarking, Computer science, CUDA, nVidia, Performance, Pseudo-random number generators, Tesla T10

June 5, 2011 by hgpu

Impact of the Random Number generator quality on particle swarm optimization algorithm running on graphic processor units

C.J.A. Bastos-Filho, M.A.C. Oliveira, D.N.O. Nascimento, A.D. Ramos

Tags: Algorithms, Computer science, Optimization, Pseudo-random number generators

May 31, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

ShoveRand: a model-driven framework to easily generate random numbers on GP-GPU

Parallel Random Numbers: As Easy as 1, 2, 3

A Hybrid Software Framework for the GPU Acceleration of Multi-Threaded Monte Carlo Applications

An FPGA-specific algorithm for direct generation of multi-variate Gaussian random numbers

A Variant of Mersenne Twister Suitable for Graphic Processors

High-Performance Pseudo-Random Number Generation on Graphics Processing Units

Pseudo-Random Number Generation on GP-GPU

Pseudo-random number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices

Hybrid Embarrassingly Parallel on heterogeneous platform

Fast, Processor-Cardinality Agnostic PRNG with a Tracking Application

Efficient Embarrassingly Parallel on Graphics Processor Unit

Impact of the Random Number generator quality on particle swarm optimization algorithm running on graphic processor units

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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