high performance computing on graphics processing units: hgpu.org

Daniel L. Ayres, Aaron Darling, Derrick J. Zwickl, Peter Beerli, Mark T. Holder, Paul O. Lewis, John P. Huelsenbeck, Fredrik Ronquist, David L. Swofford, Michael P. Cummings, Andrew Rambaut, Marc A. Suchard

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Tags: Bayesian, Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 580

October 25, 2011 by hgpu

gpustats: GPU Library for Statistical Computing in Python

Andrew Cron, Wes McKinney

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Tags: Algorithms, Bayesian, Code generation, CUDA, Mathematics, nVidia, nVidia GeForce GTS 250, OpenCL, Package, Probability, Python, Statistics

October 13, 2011 by hgpu

A Generic Approach to Topic Models

Gregor Heinrich

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Tags: Algorithms, Bayesian, Computer science

September 16, 2011 by hgpu

Wavelet Model-based Stereo for Fast, Robust Face Reconstruction

Alan Brunton, Jochen Lang, Eric Dubois, Chang Shu

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Tags: Algorithms, Bayesian, Cloud, Computer science, Computer vision, CUDA, GLSL, nVidia, OpenGL, Wavelet

July 23, 2011 by hgpu

Parallel grid-based recursive Bayesian estimation using GPU for real-time autonomous navigation

Tomonari Furukawa, Benjamin Lavis, Hugh F. Durrant-Whyte

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Tags: Bayesian, Computer science, nVidia, nVidia GeForce 8800 GTS

May 3, 2011 by hgpu

Bridging the GPGPU-FPGA efficiency gap

Christopher W. Fletcher, Ilia A. Lebedev, Narges B. Asadi, Daniel R. Burke, John Wawrzynek

Tags: Algorithms, Bayesian, Computer science, FPGA, Heterogeneous systems, nVidia, OpenCL

March 22, 2011 by hgpu

MrBayes on a Graphics Processing Unit

Jianfu Zhou, Xiaoguang Liu, Douglas S. Stones, Qiang Xie, Gang Wang

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Tags: Bayesian, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 480, Package

March 18, 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

Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization

Turbo Bayesian Compressed Sensing

cudaBayesreg: Parallel Implementation of a Bayesian Multilevel Model for fMRI Data Analysis

Acceleration Methods for Bayesian Network Sampling

Exploring Many-Core Design Templates for FPGAs and ASICs

BEAGLE: an Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

gpustats: GPU Library for Statistical Computing in Python

A Generic Approach to Topic Models

Parallel grid-based recursive Bayesian estimation using GPU for real-time autonomous navigation

Bridging the GPGPU-FPGA efficiency gap

MrBayes on a Graphics Processing Unit

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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