high performance computing on graphics processing units: hgpu.org

James Bergstra, Frederic Bastien, Olivier Breuleux, Pascal Lamblin, Razvan Pascanu, Olivier Delalleau, Guillaume Desjardins, David Warde-Farley, Ian Goodfellow, Arnaud Bergeron, Yoshua Bengio

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Package, Python

January 16, 2012 by hgpu

BarraCUDA – a fast short read sequence aligner using graphics processing units

Petr Klus, Simon Lam, Dag Lyberg, Ming Sin Cheung, Graham Pullan, Ian McFarlane, Giles S. H. Yeo, Brian Y. H. Lam

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Sequence alignment, Tesla M2050, Tesla M2090

January 13, 2012 by hgpu

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

Haixiang Shi, Bertil Schmidt, Weiguo Liu, Wolfgang Muller-Wittig

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Tags: Algorithms, Biology, Computational biology, CUDA, Image processing, Machine learning, nVidia, Package, Tesla C2050

January 13, 2012 by hgpu

MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

Peng Jia, Liming Xuan, Lei Liu, Chaochun Wei

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Tags: Biology, Computational biology, CUDA, Genetics, nVidia, Package, Tesla C1060

January 11, 2012 by hgpu

Report on the Feasibility of Implementing PIC Codes on a GPU

Joshua Payne

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Tags: CUDA, nVidia, nVidia GeForce GTX 470, Package, Physics, Plasma physics

January 7, 2012 by hgpu

CodePy

Martin Kempf

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Python

January 6, 2012 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Packages

EASEA: A Generic Optimization Tool for GPU Machines in Asynchronous Island Model

Accelerated Large-Scale Multiple Sequence Alignment

A Template Metaprogramming Approach to Support Parallel Programs for Multicores

Programming on Parallel Machines: GPU, Multicore, Clusters and More

A Modular System Architecture for Online Parallel Vision Pipelines

Theano: Deep Learning on GPUs with Python

BarraCUDA – a fast short read sequence aligner using graphics processing units

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

Report on the Feasibility of Implementing PIC Codes on a GPU

CodePy

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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