Pseudo-random number generators | Page 5

hgpu.org » Pseudo-random number generators

Statistical testing of random number sequences using CUDA

Alin Suciu, Lidia Zegreanu, Catalin Tudor Zima

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

April 16, 2011 by hgpu

GPU Random Numbers via the Tiny Encryption Algorithm

Fahad Zafar, Marc Olano, Aaron Curtis

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 M GT, nVidia GeForce 9800 GT, Pseudo-random number generators

March 23, 2011 by hgpu

A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation

David Barrie Thomas, Lee Howes, Wayne Luk

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Pseudo-random number generators

March 20, 2011 by hgpu

Mersenne Twister Random Number Generation on FPGA, CPU and GPU

Xiang Tian, Khaled Benkrid

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 8800 GTX, Pseudo-random number generators

March 20, 2011 by hgpu

Pseudorandom number generation on the GPU

Myles Sussman, William Crutchfield, Matthew Papakipos

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Tags: Algorithms, ATI, ATI Radeon X1900, Computer science, DirectX, HLSL, Presentation, Pseudo-random number generators

March 11, 2011 by hgpu

GPU Accelerated Scalable Parallel Random Number Generators

Shuang Gao, Gregory D. Peterson

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Tags: Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 480, Pseudo-random number generators, Tesla S1060

February 19, 2011 by hgpu

PRNG Random Numbers on GPU

W. B. Langdon

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Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Pseudo-random number generators, RapidMind

February 15, 2011 by hgpu

A Fast High Quality Pseudo Random Number Generator for Graphics Processing Units

W. B. Langdon

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Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Pseudo-random number generators, RapidMind

February 15, 2011 by hgpu

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

K.A. Hawick, A. Leist, and D.P. Playne

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Tags: Cell processor, Computer science, CUDA, Data parallelism, Finite difference, nVidia, nVidia GeForce GTX 295, OpenCL, Partial differential equations, PDEs, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

Comparing Intra- and Inter-Processor Parallelism on Multi-Core Cell Processors for Scientific Simulations

K.A. Hawick, A. Leist and D.P. Playne and M.J. Johnson

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Tags: Cell processor, Computer science, Playstation, Pseudo-random number generators

February 14, 2011 by hgpu

Speed and Portability issues for Random Number Generation on Graphical Processing Units with CUDA and other Processing Accelerators

K.A. Hawick, A. Leist, D.P. Playne, M.J. Johnson

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Tags: Cell processor, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, Pseudo-random number generators

February 13, 2011 by hgpu

Using graphics processing units to generate random numbers

S. Hissoiny, P. Despres, B. Ozell

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Tags: CUDA, nVidia, nVidia GeForce GTX 280, Physics, Pseudo-random number generators

January 12, 2011 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Statistical testing of random number sequences using CUDA

GPU Random Numbers via the Tiny Encryption Algorithm

A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation

Mersenne Twister Random Number Generation on FPGA, CPU and GPU

Pseudorandom number generation on the GPU

GPU Accelerated Scalable Parallel Random Number Generators

PRNG Random Numbers on GPU

A Fast High Quality Pseudo Random Number Generator for Graphics Processing Units

Mixing Multi-Core CPUs and GPUs for Scientific Simulation Software

Comparing Intra- and Inter-Processor Parallelism on Multi-Core Cell Processors for Scientific Simulations

Speed and Portability issues for Random Number Generation on Graphical Processing Units with CUDA and other Processing Accelerators

Using graphics processing units to generate random numbers

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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