high performance computing on graphics processing units: hgpu.org

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Statistical Computing With Graphics Processing Units

Ruoyong Xu

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Tags: Computer science, Package, Pseudo-random number generators, R, Statistics, Thesis

March 19, 2023 by hgpu

GPU-accelerated Gibbs Sampling

Alexander Terenin, Shawfeng Dong, David Draper

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Tags: Bayesian, big data, CUDA, nVidia, Statistics, Tesla K20

August 18, 2016 by hgpu

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

Kevin L. Keys, Gary K. Chen, Kenneth Lange

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Tags: Bioinformatics, Genetics, Machine learning, nVidia, OpenCL, Package, Statistics, Tesla C2050

August 8, 2016 by hgpu

Multi-dimensional Functional Principal Component Analysis

Lu-Hung Chen, Ci-Ren Jiang

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Tags: FFT, nVidia, nVidia GeForce GTX 980, nVidia Quadro K600, OpenACC, Statistics

October 16, 2015 by hgpu

Partitioning Large Scale Deep Belief Networks Using Dropout

Yanping Huang, Sai Zhang

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Tags: Benchmarking, Databases, Deep learning, Machine learning, nVidia, nVidia GeForce 8800 GS, Python, Statistics

August 31, 2015 by hgpu

Accelerated dimension-independent adaptive Metropolis

Yuxin Chen, David Keyes, Kody J.H. Law, Hatem Ltaief

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Tags: CUDA, nVidia, Probability, Statistics, Tesla K40

June 19, 2015 by hgpu

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

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Tags: Algorithms, Biology, CUDA, Genetics, Machine learning, Neuroscience, nVidia, nVidia GeForce GTX Titan, Statistics

September 9, 2014 by hgpu

Bayesian model comparison via sequential Monte Carlo

Yan Zhou

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Tags: Algorithms, Bayesian, Mathematics, nVidia, nVidia Quadro 2000, OpenCL, Package, Statistics, Thesis

July 28, 2014 by hgpu

Fast Hamiltonian Monte Carlo Using GPU Computing

Andrew L. Beam, Sujit K. Ghosh, Jon Doyle

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Tags: Algorithms, Bayesian, CUDA, CULA, Monte Carlo simulation, nVidia, Package, Python, Statistics, Tesla K20

February 19, 2014 by hgpu

Graphics Processing Units in Acceleration of Bandwidth Selection for Kernel Density Estimation

Witold Andrzejewski, Artur Gramacki, Jaroslaw Gramacki

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Tags: Algorithms, CUDA, nVidia, nVidia GeForce GTX 480, Package, Probability, Statistics

December 24, 2013 by hgpu

Augur: a Modeling Language for Data-Parallel Probabilistic Inference

Jean-Baptiste Tristan, Daniel Huang, Joseph Tassarotti, Adam Pocock, Stephen J. Green, Guy L. Steele Jr

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Tags: Bayesian, CUDA, Machine learning, Mathematics, nVidia, nVidia GeForce GTX Titan, Programming Languages, Statistics

December 13, 2013 by hgpu

SIMD Parallel Gibbs Sampling of Probabilistic Directed Acyclic Graphs

Alireza S. Mahani, Mansour T.A. Sharabiani

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Tags: Artificial intelligence, Bayesian, Intel Phi, Intel Xeon Phi, OpenMP, Statistics

October 22, 2013 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Statistical Computing With Graphics Processing Units

GPU-accelerated Gibbs Sampling

Iterative Hard Thresholding for Model Selection in Genome-Wide Association Studies

Multi-dimensional Functional Principal Component Analysis

Partitioning Large Scale Deep Belief Networks Using Dropout

Accelerated dimension-independent adaptive Metropolis

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Bayesian model comparison via sequential Monte Carlo

Fast Hamiltonian Monte Carlo Using GPU Computing

Graphics Processing Units in Acceleration of Bandwidth Selection for Kernel Density Estimation

Augur: a Modeling Language for Data-Parallel Probabilistic Inference

SIMD Parallel Gibbs Sampling of Probabilistic Directed Acyclic Graphs

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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