high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

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

Data Transfer Matters for GPU Computing

Yusuke Fujii, Takuya Azumi, Nobuhiko Nishio, Shinpei Kato, Masato Edahiro

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

December 13, 2013 by hgpu

Development of Bayesian analysis program for extraction of polarisation observables at CLAS

S. Lewis, D. Ireland, W. Vanderbauwhede

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Tags: ATI, Bayesian, OpenCL, Package, Physics

December 12, 2013 by hgpu

Efficient Large-Scale Graph Processing on Hybrid CPU and GPU Systems

Abdullah Gharaibeh, Elizeu Santos-Neto, Lauro Beltrao Costa, Matei Ripeanu

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, Hybrid computing, nVidia, Package

December 12, 2013 by hgpu

Learning Random Forests on the GPU

Yisheng Liao, Alex Rubinsteyn, Russell Power, Jinyang Li

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX Titan, Package, Tesla C2075

December 11, 2013 by hgpu

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

P. Berczik, R. Spurzem, L. Wang, S. Zhong, O. Veles, I. Zinchenko, S. Huang, M. Tsai, G. Kennedy, S. Li, L. Naso, C. Li

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Tags: Astrophysics, CUDA, GPU cluster, MPI, N-body simulation, nVidia, Package, Tesla C2050, Tesla K20

December 9, 2013 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Applications

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

Data Transfer Matters for GPU Computing

Development of Bayesian analysis program for extraction of polarisation observables at CLAS

Efficient Large-Scale Graph Processing on Hybrid CPU and GPU Systems

Learning Random Forests on the GPU

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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