high performance computing on graphics processing units: hgpu.org

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Graphics hardware & GPU computing: past, present, and future

David Luebke

Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce GTX 280, Review

May 4, 2011 by hgpu

Accelerating scientific applications using GPU’s

M. Taher

Tags: Bioinformatics, Biology, Computer science, CUDA, FFT, nVidia, Security, Sequence alignment

May 3, 2011 by hgpu

GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction

Vu Pham, Phong Vo, Vu Thanh Hung, Le Hoai Bac

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Source codes

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 9600 GT, Package

May 3, 2011 by hgpu

Statistical power modeling of GPU kernels using performance counters

Hitoshi Nagasaka, Naoya Maruyama, Akira Nukada, Toshio Endo, Satoshi Matsuoka

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 285

May 3, 2011 by hgpu

Realtime Simulation of Burning Solids on GPU with CUDA

Jian Zhu, Youquan Liu, Kai Bao, Yuanzhang Chang, Enhua Wu

Tags: CUDA, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia

May 3, 2011 by hgpu

Exploiting GPU On-chip Shared Memory for Accelerating Schedulability Analysis

Swaroop Nunna, Unmesh D. Bordoloi, Samarjit Chakraborty, Petru Eles, Zebo Peng

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce 8800 GTX

May 3, 2011 by hgpu

GPU based acceleration architecture for image enhancement in spatial domain

Li Zhonghua, Zhou Fugen, Bai Xiangzhi

Tags: Algorithms, CUDA, Image processing, nVidia

May 3, 2011 by hgpu

Reconfigurable real-time MIMO detector on GPU

Michael Wu, Yang Sun, Joseph R. Cavallaro

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Tags: Algorithms, Computer science, CUDA, MIMO, nVidia, nVidia GeForce 9600 GT

April 30, 2011 by hgpu

GPU-based simulation of cellular neural networks for image processing

R. Dolan, G. DeSouza

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Tags: Cellular neural networks, CUDA, Image processing, nVidia

April 30, 2011 by hgpu

GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images

Xiao-Xi Chen, Ming-Hui Shi, H. de Garis

Tags: Computer science, Computer vision, CUDA, Image recognition, Neural networks, nVidia

April 30, 2011 by hgpu

EcoG: A Power-Efficient GPU Cluster Architecture for Scientific Computing

Mike Showerman, Jeremy Enos, Craig Steffen, Sean Treichler, William Gropp, Wen-mei W. Hwu

Tags: Computer science, CUDA, Energy-efficient computing, GPU cluster, nVidia

April 30, 2011 by hgpu

Pushing the limits for medical image reconstruction on recent standard multicore processors

Jan Treibig, Georg Hager, Hannes G. Hofmann, Joachim Hornegger, Gerhard Wellein

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Tags: Computed tomography, Computer science, CT, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX 260, nVidia Quadro FX 5800, OpenMP, Performance

April 29, 2011 by hgpu

Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Graphics hardware & GPU computing: past, present, and future

Accelerating scientific applications using GPU’s

GPU Implementation of Extended Gaussian Mixture Model for Background Subtraction

Statistical power modeling of GPU kernels using performance counters

Realtime Simulation of Burning Solids on GPU with CUDA

Exploiting GPU On-chip Shared Memory for Accelerating Schedulability Analysis

GPU based acceleration architecture for image enhancement in spatial domain

Reconfigurable real-time MIMO detector on GPU

GPU-based simulation of cellular neural networks for image processing

GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images

EcoG: A Power-Efficient GPU Cluster Architecture for Scientific Computing

Pushing the limits for medical image reconstruction on recent standard multicore processors

Recent source codes

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

INT v.s. FP: A framework to compare low-bit integer and float-point formats

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

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

Kernel Library for LLM Serving

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

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