high performance computing on graphics processing units: hgpu.org

Packages

hgpu.org » Applications

Nengo: a Python tool for building large-scale functional brain models

Trevor Bekolay, James Bergstra, Eric Hunsberger, Travis DeWolf, Terrence C. Stewart, Daniel Rasmussen, Xuan Choo, Aaron Russell Voelker, Chris Eliasmith

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Tags: ATI, ATI Radeon HD 7970, Biology, Neuroscience, nVidia, nVidia GeForce GTX 280, OpenCL, Package, PyOpenCL, Python

January 9, 2014 by hgpu

The Parallel Bayesian Toolbox for High-performance Bayesian Filtering in Metrology

E. Garcia, T. Hausotte

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Tags: Algorithms, Bayesian, CUDA, Filtering, nVidia, Package, Particle filtering, Physics, Probability, Tesla C2075

January 6, 2014 by hgpu

PySPH: A Python framework for SPH

Kunal Puri, Prabhu Ramachandran, Pankaj Pandey, Chandrashekhar Kaushik, Pushkar Godbole

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Tags: Fluid dynamics, OpenCL, Package, Python

January 6, 2014 by hgpu

Parallel Irradiance Caching on the GPU

Nathaniel L. Jones

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Tags: Computer science, CUDA, nVidia, nVidia Quadro K4000, OptiX, Package, Raytracing

January 5, 2014 by hgpu

Accelerating Simulation Codes through the GeMTC Framework

Digvijay Singh Gahlot, Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Performance

January 3, 2014 by hgpu

Nemo: A parallelized Lagrangian particle-tracking model

Benjamin Jones

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Tags: CUDA, Earth and Space Sciences, Fortran, MPI, nVidia, nVidia GeForce GTX 650 M, Package

January 3, 2014 by hgpu

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

Pinghao Li, Xiaoqian Jiang, Shuang Wang, Jihoon Kim, Hongkai Xiong, Lucila Ohno-Machado

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Tags: Algorithms, Bioinformatics, Biology, Clustering, Compression, CUDA, nVidia, Package, Sequence alignment, Tesla M2090

December 27, 2013 by hgpu

BbmTTP: Beat-based Parallel Simulated Annealing Algorithm on GPGPUs for the Mirrored Traveling Tournament Problem

Vijay Menon, Saurabh Jha

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Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, Package, Tesla M2050

December 27, 2013 by hgpu

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Tetsuya Odajima, Taisuke Boku, Mitsuhisa Sato, Toshihiro Hanawa, Yuetsu Kodama, Raymond Namyst, Samuel Thibault, Olivier Aumage

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Performance, Task scheduling, Tesla M2090

December 25, 2013 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

Warps and Atomics: Beyond Barrier Synchronization in the Verification of GPU Kernels

Ethel Bardsley, Alastair F. Donaldson

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Package, Python

December 20, 2013 by hgpu

Data Structures for Task-based Priority Scheduling

Martin Wimmer, Daniel Cederman, Francesco Versaci, Jesper Larsson Traff, Philippas Tsigas

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Tags: Algorithms, Computer science, Intel Xeon Phi, Package, Task scheduling

December 17, 2013 by hgpu

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

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high performance computing on graphics processing units: hgpu.org

Packages

Nengo: a Python tool for building large-scale functional brain models

The Parallel Bayesian Toolbox for High-performance Bayesian Filtering in Metrology

PySPH: A Python framework for SPH

Parallel Irradiance Caching on the GPU

Accelerating Simulation Codes through the GeMTC Framework

Nemo: A parallelized Lagrangian particle-tracking model

HUGO: Hierarchical mUlti-reference Genome cOmpression for aligned reads

BbmTTP: Beat-based Parallel Simulated Annealing Algorithm on GPGPUs for the Mirrored Traveling Tournament Problem

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

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

Warps and Atomics: Beyond Barrier Synchronization in the Verification of GPU Kernels

Data Structures for Task-based Priority Scheduling

Recent source codes

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

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