high performance computing on graphics processing units: hgpu.org

hgpu.org » Bayesian

MrBayes on a Graphics Processing Unit

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

Source codes

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

March 18, 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

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

March 4, 2011 by hgpu

Efficient Bayesian inference in stochastic chemical kinetic models using graphical processing units

Jarad Niemi, Matthew Wheeler

View

Download (PDF)

Tags: Bayesian, Biology, Chemistry, CUDA, nVidia, Stochastic simulation, Tesla T10

January 26, 2011 by hgpu

High-throughput bayesian computing machine with reconfigurable hardware

Mingjie Lin, Ilia Lebedev, John Wawrzynek

View

Download (PDF)

Tags: Bayesian, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 9400 M

January 9, 2011 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

MrBayes on a Graphics Processing Unit

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

Efficient Bayesian inference in stochastic chemical kinetic models using graphical processing units

High-throughput bayesian computing machine with reconfigurable hardware

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)