high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Mathematics » Statistics

Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors

Anthony Lee, Francois Caron, Arnaud Doucet, Chris Holmes

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Tags: CUDA, Mathematics, nVidia, nVidia GeForce 8800 GT, Statistics

June 3, 2011 by hgpu

The fast evaluation of hidden Markov models on GPU

Jun Li, Shuangping Chen, Yanhui Li

Tags: Algorithms, Computer science, nVidia, nVidia GeForce 9800 GTX, Statistics

April 12, 2011 by hgpu

Data Assimilation using a GPU Accelerated Path Integral Monte Carlo Approach

John C. Quinn, Henry D. I. Abarbanel

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Tags: Computational Physics, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 460, Physics, Probability, Statistics

March 28, 2011 by hgpu

Some of the What?, Why?, How?, Who? and Where? of Graphics Processing Unit Computing for Bayesian Analysis

Marc A. Suchard, Chris Holmes, Mike West

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Tags: Bayesian, CUDA, Mathematics, nVidia, Review, Statistics

March 4, 2011 by hgpu

Understanding GPU Programming for Statistical Computation: Studies in Massively Parallel Massive Mixtures

Marc A. Suchard, Quanli Wang, Cliburn Chan, Jacob Frelinger, Andrew Cron, Mike West

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Tags: Bayesian, CUDA, Mathematics, nVidia, nVidia GeForce 9600 M GT, nVidia GeForce GTX 285, Package, Statistics, Tesla C1060

March 4, 2011 by hgpu

High-throughput Bayesian network learning using heterogeneous multicore computers

Michael D. Linderman, Robert Bruggner, Vivek Athalye, Teresa H. Meng, Narges B. Asadi, Garry P. Nolan

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Tags: Algorithms, CUDA, GPU cluster, Mathematics, nVidia, nVidia GeForce GTX 285, Statistics, Tesla C1060, Tesla S1070

December 15, 2010 by hgpu

A Markovian event-based framework for stochastic spiking neural networks

Jonathan Touboul, Olivier Faugeras

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Tags: Algorithms, Mathematics, Neural networks, Neurons and Cognition, Statistics, Statistics Theory

November 13, 2010 by hgpu

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Anthony Lee, Christopher Yau, Michael B. Giles, Arnaud Doucet, Christopher C. Holmes

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Tags: CUDA, Mathematics, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Statistics

November 8, 2010 by hgpu

Graphics Processing Units and High-Dimensional Optimization

Hua Zhou, Kenneth Lange, Marc A. Suchard

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Tags: Block relaxation, CUBLAS, CUDA, EM and MM algorithms, Mathematics, Multidimensional scaling, Nonnegative matrix factorization, nVidia, nVidia GeForce GTX 280, PET scanning, Statistics

October 30, 2010 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

Applications

Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors

The fast evaluation of hidden Markov models on GPU

Data Assimilation using a GPU Accelerated Path Integral Monte Carlo Approach

Some of the What?, Why?, How?, Who? and Where? of Graphics Processing Unit Computing for Bayesian Analysis

Understanding GPU Programming for Statistical Computation: Studies in Massively Parallel Massive Mixtures

High-throughput Bayesian network learning using heterogeneous multicore computers

A Markovian event-based framework for stochastic spiking neural networks

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Graphics Processing Units and High-Dimensional Optimization

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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