high performance computing on graphics processing units: hgpu.org

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Staggered fermions simulations on GPUs

Claudio Bonati, Guido Cossu, Massimo D'Elia, Adriano Di Giacomo

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, Physics, QCD, Tesla C1060, Tesla C2050

November 9, 2010 by hgpu

Parallelizing the QUDA Library for Multi-GPU Calculations in Lattice Quantum Chromodynamics

Ronald Babich, Michael A. Clark, Balint Joo

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package, Physics, QCD, Tesla C1060, Tesla C2050, Tesla C870

November 9, 2010 by hgpu

Numerical modeling of gravitational wave sources accelerated by OpenCL

Gaurav Khanna, Justin McKennon

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Tags: Cell processor, Computational Physics, General Relativity and Quantum Cosmology, Gravitation, nVidia, OpenCL, Physics, Tesla C1060

November 9, 2010 by hgpu

A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

Marius Buibas, Gabriel A. Silva

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Tags: Biological Physics, Condensed matter, CUDA, Disordered Systems and Neural Networks, Mathematical Physics, Neurons and Cognition, nVidia, Package, Physics, Tesla C1060

November 9, 2010 by hgpu

An exploration of CUDA and CBEA for a gravitational wave source-modelling application

Gaurav Khanna, Justin McKennon

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Tags: Cell processor, CUDA, General Relativity and Quantum Cosmology, Gravitation, nVidia, Physics, Tesla C1060

November 9, 2010 by hgpu

Gravitational tree-code on graphics processing units: implementation in CUDA

Evghenii Gaburov, Jeroen Bedorf, Simon P. Zwart

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 8800 Ultra, Package, Physics

November 9, 2010 by hgpu

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

A. Zhmurov, K. Rybnikov, Y. Kholodov, V. Barsegov

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Tags: Biological Physics, Chemical Physics, CUDA, nVidia, nVidia GeForce GTX 295, Physics, Pseudo-random number generators

November 9, 2010 by hgpu

Viewpoints: A high-performance high-dimensional exploratory data analysis tool

P.R. Gazis, C. Levit, M.J.Way

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Tags: Astrophysics, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 7950 GTX, OpenGL, Physics, Statistics and Probability, Visualization

November 9, 2010 by hgpu

Analysing Astronomy Algorithms for GPUs and Beyond

Benjamin R. Barsdell, David G. Barnes, Christopher J. Fluke

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Tags: Algorithms, Astrophysics, Instrumentation and Methods for Astrophysics, Physics

November 8, 2010 by hgpu

Integrating Post-Newtonian Equations on Graphics Processing Units

Frank Herrmann, John Silberholz, Matias Bellone, Gustavo Guerberoff, Manuel Tiglio

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Earth and Planetary Astrophysics, Galaxy Astrophysics, General Relativity and Quantum Cosmology, High Energy Astrophysical Phenomena, Instrumentation and Methods for Astrophysics, nVidia, Physics, Solar and Stellar Astrophysics, Tesla S1070

November 8, 2010 by hgpu

Graphic-Card Cluster for Astrophysics (GraCCA) – Performance Tests

Hsi-Yu Schive, Chia-Hung Chien, Shing-Kwong Wong, Yu-Chih Tsai, Tzihong Chiueh

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Tags: Astrophysics, CUDA, GPU cluster, Gravitation, MPI, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Physics, Stellar dynamics

November 8, 2010 by hgpu

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

K. Hagiwara, J. Kanzaki, N. Okamura, D. Rainwater, T. Stelzer

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Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, nVidia, nVidia GeForce GTX 280, Physics

November 8, 2010 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

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high performance computing on graphics processing units: hgpu.org

Staggered fermions simulations on GPUs

Parallelizing the QUDA Library for Multi-GPU Calculations in Lattice Quantum Chromodynamics

Numerical modeling of gravitational wave sources accelerated by OpenCL

A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

An exploration of CUDA and CBEA for a gravitational wave source-modelling application

Gravitational tree-code on graphics processing units: implementation in CUDA

Efficient pseudo-random number generators for biomolecular simulations on graphics processors

Viewpoints: A high-performance high-dimensional exploratory data analysis tool

Analysing Astronomy Algorithms for GPUs and Beyond

Integrating Post-Newtonian Equations on Graphics Processing Units

Graphic-Card Cluster for Astrophysics (GraCCA) – Performance Tests

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

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

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