high performance computing on graphics processing units: hgpu.org

hgpu.org » Bayesian

GPU-accelerated Gibbs Sampling

Alexander Terenin, Shawfeng Dong, David Draper

View

Download (PDF)

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

August 18, 2016 by hgpu

Fast Predictive Image Registration

Xiao Yang, Roland Kwitt, Marc Niethammer

View

Download (PDF)

Source codes

Tags: Bayesian, Computer science, Computer vision, CUDA, Deep learning, Image registration, nVidia, nVidia GeForce GTX Titan X, Package, Python

July 11, 2016 by hgpu

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

Tetsuya Takaishi

View

Download (PDF)

Tags: Bayesian, Computational finance, CUDA, Finance, Fortran, nVidia, nVidia GeForce GTX 760, OpenACC

March 29, 2016 by hgpu

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

David Webb

View

Download (PDF)

Tags: Bayesian, Computer science, Computer vision, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Jetson TK1, SoC, Thesis

February 2, 2016 by hgpu

R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses

Benoit Liquet, Leonardo Bottolo, Gianluca Campanella, Sylvia Richardson, Marc Chadeau-Hyam

View

Download (PDF)

Source codes

Tags: Bayesian, Computer science, CUDA, CULA, nVidia, Package

February 1, 2016 by hgpu

A Deep Generative Deconvolutional Image Model

Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin

View

Download (PDF)

Tags: Bayesian, Caffe, Computer science, Computer vision, CUDA, Deep learning, Image generation, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

December 31, 2015 by hgpu

A General Framework for Constrained Bayesian Optimization using Information-based Search

Jose Miguel Hernandez-Lobato, Michael A. Gelbart, Ryan P. Adams, Matthew W. Hoffman, Zoubin Ghahramani

View

Download (PDF)

Source codes

Tags: Bayesian, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Package, Python

December 1, 2015 by hgpu

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Yong-Deok Kim, Eunhyeok Park, Sungjoo Yoo, Taelim Choi, Lu Yang, Dongjun Shin

View

Download (PDF)

Tags: ARM, Bayesian, Caffe, CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

November 24, 2015 by hgpu

Multi-GPU Distributed Parallel Bayesian Differential Topic Modelling

Aaron Q Li

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 5870, Bayesian, Computer science, GPU cluster, Machine learning, NLP, nVidia, nVidia GeForce GTX 480, OpenCL, Thesis

October 25, 2015 by hgpu

Fast Exact Bayesian Inference for High-Dimensional Models

Joao Filipe Ferreira, Pablo Lanillos, Jorge Dias

View

Download (PDF)

Tags: Bayesian, Computer science, Computer vision, nVidia, nVidia GeForce GTX 780, OpenCL, Robotics

September 26, 2015 by hgpu

Parallelization, Scalability, and Reproducibility in Next-Generation Sequencing Analysis

Johannes Koster

View

Download (PDF)

Source codes

Tags: Algorithms, Bayesian, Bioinformatics, Biology, Filtering, Next-Generation sequencing, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 780, OpenCL, Package, Thesis

March 23, 2015 by hgpu

Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Simon Perkins, Patrick Maraism, Jonathan Zwart, Iniyan Natarajan, Oleg Smirnov

View

Download (PDF)

Source codes

Tags: Astrophysics, Bayesian, Computer science, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Python, Tesla K40

February 2, 2015 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

GPU-accelerated Gibbs Sampling

Fast Predictive Image Registration

GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses

A Deep Generative Deconvolutional Image Model

A General Framework for Constrained Bayesian Optimization using Information-based Search

Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

Multi-GPU Distributed Parallel Bayesian Differential Topic Modelling

Fast Exact Bayesian Inference for High-Dimensional Models

Parallelization, Scalability, and Reproducibility in Next-Generation Sequencing Analysis

Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

Most viewed papers (last 30 days)