high performance computing on graphics processing units: hgpu.org

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Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors

Peter Bailey, Joe Myre, Stuart D.C. Walsh, David J. Lilja, Martin O. Saar

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia GeForce 8800 GTX, nVidia GeForce 8800 Ultra, nVidia GeForce 9800 GX2

November 27, 2010 by hgpu

Accelerating geoscience and engineering system simulations on graphics hardware

Stuart D. C. Walsh, Martin O. Saar, Peter Bailey, David J. Lilja

Tags: CUDA, Earth and Space Sciences, Geoscience, Lattice Boltzmann model, nVidia, Seismology

November 27, 2010 by hgpu

A massively parallel adaptive fast-multipole method on heterogeneous architectures

Ilya Lashuk, Aparna Chandramowlishwaran, Harper Langston, Tuan A. Nguyen, Rahul Sampath, Aashay Shringarpure, Richard Vuduc, Lexing Ying, Denis Zorin, George Biros

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Tags: Computer science, CUDA, Fast multipole method, GPU cluster, MPI, N-body simulation, nVidia, Programming techniques, Tesla S1070

November 27, 2010 by hgpu

An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Eduard Ayguade, Rosa Badia, Francisco Igual, Jesus Labarta, Rafael Mayo, Enrique Quintana-Orti

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla S1070

November 27, 2010 by hgpu

Quantum computer simulation using the CUDA programming model

Eladio Gutierrez, Sergio Romero, Maria A. Trenas, Emilio L. Zapata

Tags: Computer science, CUDA, nVidia, Quantum computing

November 27, 2010 by hgpu

Predictive Runtime Code Scheduling for Heterogeneous Architectures

Victor Jimenez, Lluis Vilanova, Isaac Gelado, Marisa Gil, Grigori Fursin, Nacho Navarro

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, Task scheduling

November 27, 2010 by hgpu

Exploiting graphical processing units for data-parallel scientific applications

A. Leist, D. P. Playne, K. A. Hawick

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Tags: Computer science, CUDA, Field equations, Graph theory, nVidia, nVidia GeForce 8800 GTS

November 27, 2010 by hgpu

CUDA-MEME: Accelerating Motif Discovery in Biological Sequences Using CUDA-enabled Graphics Processing Units

Yongchao Liu, Bertil Schmidt, Weiguo Liu, Douglas L. Maskell

Tags: Biology, CUDA, nVidia, nVidia GeForce GTX 280, Pattern recognition

November 27, 2010 by hgpu

Performance Analysis of IBM Cell Broadband Engine on Sequence Alignment

Yang Song, Gregory M. Striemer, Ali Akoglu

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Tags: Bioinformatics, Biology, Cell processor, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C870

November 27, 2010 by hgpu

Molecular dynamics simulation of complex multiphase flow on a computer cluster with GPUs

Feiguo Chen, Wei Ge, Jinghai Li

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Tags: Chemistry, CUDA, GPU cluster, Molecular dynamics, MPI, nVidia, Tesla C870

November 27, 2010 by hgpu

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Mingliang Wang, Hector Klie, Manish Parashar, Hari Sudan

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla T10P

November 27, 2010 by hgpu

Harnessing graphics processors for the fast computation of acoustic likelihoods in speech recognition

Paul R. Dixon, Tasuku Oonishi, Sadaoki Furui

Tags: Acoustics, CUDA, nVidia, Signal processing, Speech recognition

November 27, 2010 by hgpu

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

MSCCL++: A GPU-driven communication stack for scalable AI applications

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating Lattice Boltzmann Fluid Flow Simulations Using Graphics Processors

Accelerating geoscience and engineering system simulations on graphics hardware

A massively parallel adaptive fast-multipole method on heterogeneous architectures

An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Quantum computer simulation using the CUDA programming model

Predictive Runtime Code Scheduling for Heterogeneous Architectures

Exploiting graphical processing units for data-parallel scientific applications

CUDA-MEME: Accelerating Motif Discovery in Biological Sequences Using CUDA-enabled Graphics Processing Units

Performance Analysis of IBM Cell Broadband Engine on Sequence Alignment

Molecular dynamics simulation of complex multiphase flow on a computer cluster with GPUs

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Harnessing graphics processors for the fast computation of acoustic likelihoods in speech recognition

Recent source codes

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

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