high performance computing on graphics processing units: hgpu.org

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GPUQP: query co-processing using graphics processors

Rui Fang, Bingsheng He, Mian Lu, Ke Yang, Naga K. Govindaraju, Qiong Luo, Pedro V. Sander

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Review

December 4, 2010 by hgpu

GPU Computing: Programming a Massively Parallel Processor

Ian Buck

Tags: Computer science, CUDA, High-level Languages, nVidia, Review

December 4, 2010 by hgpu

Simulation of 1+1 dimensional surface growth and lattices gases using GPUs

Henrik Schulz, Geza Odor, Gergely Odor, Máté Ferenc Nagy

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Tags: ATI, ATI Radeon HD 5970, Computational Physics, CUDA, Disordered Systems and Neural Networks, nVidia, nVidia Quadro FX 5800, OpenCL, Physics, Statistical Mechanics, Tesla C1060

December 3, 2010 by hgpu

GPU-BLAST: Using graphics processors to accelerate protein sequence alignment

Panagiotis D. Vouzis, Nikolaos V. Sahinidis

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Tags: Bioinformatics, Biology, BLAST, CUDA, nVidia, Package, Sequence alignment, Tesla C2050

November 30, 2010 by hgpu

StarPU: A Unified Platform for Task Scheduling on Heterogeneous Multicore Architectures

Cedric Augonnet, Samuel Thibault, Raymond Namyst, Pierre-Andre Wacrenier

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia Quadro FX 4600, Package, Performance

November 28, 2010 by hgpu

Fast multipole methods on a cluster of GPUs for the meshless simulation of turbulence

R. Yokota, T. Narumi, R. Sakamaki, S. Kameoka, S. Obi, K. Yasuoka

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Tags: CUDA, Fast multipole method, Fluid dynamics, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce 8800 GT, Physics

November 28, 2010 by hgpu

Understanding software approaches for GPGPU reliability

Martin Dimitrov, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Stream, Brook, Computer science, CUDA, Hardware, nVidia, nVidia GeForce 8800 GTX, Performance

November 28, 2010 by hgpu

Highly accelerated feature detection in proteomics data sets using modern graphics processing units

Rene Hussong, Barbara Gregorius, Andreas Tholey, Andreas Hildebrandt

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C870

November 28, 2010 by hgpu

Scattering Points in Parallel Coordinates

Xiaoru Yuan, Peihong Guo, He Xiao, Hong Zhou, Huamin Qu

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Tags: Computer science, CUDA, Multidimensional scaling, nVidia, Tesla C870, Visualization

November 28, 2010 by hgpu

Exploring Reconfigurable Architectures for Tree-Based Option Pricing Models

Qiwei Jin, David B. Thomas, Wayne Luk, Benjamin Cope

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Tags: CUDA, Finance, FPGA, nVidia, nVidia GeForce 7900 GTX

November 28, 2010 by hgpu

42 TFlops hierarchical N-body simulations on GPUs with applications in both astrophysics and turbulence

Tsuyoshi Hamada, Tetsu Narumi, Rio Yokota, Kenji Yasuoka, Keigo Nitadori, Makoto Taiji

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Tags: Astrophysics, CUDA, Fast multipole method, N-body simulation, nVidia, nVidia GeForce 8800 GTS, Performance

November 28, 2010 by hgpu

On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs

Fang Xu, Wei Xu, Mel Jones, Bettina Keszthelyi, John Sedat, David Agard, Klaus Mueller

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Tags: Cg, Computed tomography, CT, CUDA, Image reconstruction, Medicine, nVidia, nVidia GeForce 8800 GTX

November 28, 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

GPUQP: query co-processing using graphics processors

GPU Computing: Programming a Massively Parallel Processor

Simulation of 1+1 dimensional surface growth and lattices gases using GPUs

GPU-BLAST: Using graphics processors to accelerate protein sequence alignment

StarPU: A Unified Platform for Task Scheduling on Heterogeneous Multicore Architectures

Fast multipole methods on a cluster of GPUs for the meshless simulation of turbulence

Understanding software approaches for GPGPU reliability

Highly accelerated feature detection in proteomics data sets using modern graphics processing units

Scattering Points in Parallel Coordinates

Exploring Reconfigurable Architectures for Tree-Based Option Pricing Models

42 TFlops hierarchical N-body simulations on GPUs with applications in both astrophysics and turbulence

On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs

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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