high performance computing on graphics processing units: hgpu.org

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Parallel smoothing of quad meshes

Young Yeo, Tianyun Ni, Ashish Myles, Vineet Goel, Jorg Peters

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Tags: 3D Graphics and Realism, Computer science, DirectX, nVidia, nVidia GeForce 8800 GTX, Shaders, Visualization

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

Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects

Emmanuel Agullo, Jim Demmel, Jack Dongarra, Bilel Hadri, Jakub Kurzak, Julien Langou, Hatem Ltaief, Piotr Luszczek, Stanimire Tomov

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Tags: Algorithms, Computer science, Linear Algebra, Matrix multiplication

November 27, 2010 by hgpu

The multikernel: a new OS architecture for scalable multicore systems

Andrew Baumann, Paul Barham, Pierre E. Dagand, Tim Harris, Rebecca Isaacs, Simon Peter, Timothy Roscoe, Adrian Schüpbach, Akhilesh Singhania

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Tags: Computer science, Operating systems

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

The Virtual Marathon: Parallel Computing Supports Crowd Simulations

Erdal Yilmaz, Veysi Isler, Yasemin Y. Cetin

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Tags: Computer science, nVidia, nVidia GeForce GTX 280, OpenGL, Visualization

November 27, 2010 by hgpu

Accuracy and performance of graphics processors: A Quantum Monte Carlo application case study

Jeremy S. Meredith, Gonzalo Alvarez, Thomas A. Maier, Thomas C. Schulthess, Jeffrey S. Vetter

Tags: Computer science, Monte Carlo simulation, Performance

November 27, 2010 by hgpu

Triangular matrix inversion on Graphics Processing Unit

Florian Ries, Tommaso De Marco, Matteo Zivieri, Roberto Guerrieri

Tags: Computer science, CUDA, Linear Algebra, Matrix inversion, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295

November 26, 2010 by hgpu

Fast Disk Encryption through GPGPU Acceleration

Giovanni Agosta, Alessandro Barenghi, Fabrizio D. Santis, Andrea D. Biagio, Gerardo Pelosi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Package, Security

November 26, 2010 by hgpu

On the energy efficiency of graphics processing units for scientific computing

S. Huang, S. Xiao, W. Feng

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 280

November 26, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

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

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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high performance computing on graphics processing units: hgpu.org

Applications

Parallel smoothing of quad meshes

Quantum computer simulation using the CUDA programming model

Predictive Runtime Code Scheduling for Heterogeneous Architectures

Exploiting graphical processing units for data-parallel scientific applications

Numerical linear algebra on emerging architectures: The PLASMA and MAGMA projects

The multikernel: a new OS architecture for scalable multicore systems

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

The Virtual Marathon: Parallel Computing Supports Crowd Simulations

Accuracy and performance of graphics processors: A Quantum Monte Carlo application case study

Triangular matrix inversion on Graphics Processing Unit

Fast Disk Encryption through GPGPU Acceleration

On the energy efficiency of graphics processing units for scientific computing

Recent source codes

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

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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