high performance computing on graphics processing units: hgpu.org

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Issues in Heterogenenous GPU Clusters

Patrick Carpenter, William Symon

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Tags: Computer science, GPU cluster, Heterogeneous systems, Review

November 21, 2011 by hgpu

Grids, Clouds and Virtualization

Massimo Cafaro, Giovanni Aloisio (Eds.)

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Tags: Book, Cloud, Computer science, CUDA, Grid, nVidia, Review, Tesla M1060, Virtualization

November 16, 2011 by hgpu

A Preliminary Review of Literature on Parallel Constraint Solving

Ian P. Gent, Chris Jefferson, Ian Miguel, Neil C.A. Moore, Peter Nightingale, Patrick Prosser, Chris Unsworth

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Tags: Computer science, Programming techniques, Review

November 1, 2011 by hgpu

Programming Massively Parallel Processors with CUDA (audio course)

David B. Kirk, Wen-Mei W. Hwu

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Tags: Book, Computer science, CUDA, nVidia, OpenCL, Package, Programming techniques, Review, Tutorial

October 28, 2011 by hgpu

Current and Nascent SETI Instruments in the Radio and Optical

A. P. V. Siemion, J. Cobb, T. Filiba, A. Fries, A. Howard, J. von Korff, E. Korpela, M. Lebofsky, W. Mallard, A. Parsons, M. Wagner, D. Werthimer, H. Chen, P. L. McMahon, J. Cordes, L. Spitler

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Tags: Astrophysics, Heterogeneous systems, Review

October 25, 2011 by hgpu

Computational Biology and Applied Bioinformatics

Heitor Silverio Lopes, Leonardo Magalhaes Cruz

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Tags: Bioinformatics, Biology, Book, Computational biology, CUDA, nVidia, Review, Sequence alignment, Spectrometry

October 23, 2011 by hgpu

CUDA Application Design and Development

Rob Farber

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Tags: Book, Computer science, CUDA, nVidia, Review, Software Engineering

October 22, 2011 by hgpu

Computational Fluid Dynamics Using Graphics Processing Units: Challenges and Opportunities

S. Pratap Vanka, Aaron F. Shinn, Kirti C. Sahu

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Review, Tesla C1060

October 21, 2011 by hgpu

GPU Accelerated X-Ray Image Enhancement

Mark James Brotherton

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Tags: Algorithms, DirectX, HLSL, Image processing, OpenMP, Review, Thesis

October 20, 2011 by hgpu

Heterogeneous Accelerated Bioinformatics-Perspectives for Cancer Research

Eric A. Stahlberg, T. Steinke, M. C. Smith, S. Chandrasekaran, B. Chapman

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Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, Medicine, nVidia, OpenCL, Review

October 19, 2011 by hgpu

The GPU Computing Revolution: From Multi-Core CPUs To Many-Core Graphics Processors

Simon McIntosh-Smith

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Review, Tesla C2050

October 19, 2011 by hgpu

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

Christian Motzing

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Tags: Computer science, CUDA, Molecular dynamics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Review, Software Engineering, Thesis

October 17, 2011 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Issues in Heterogenenous GPU Clusters

A Preliminary Review of Literature on Parallel Constraint Solving

Programming Massively Parallel Processors with CUDA (audio course)

Current and Nascent SETI Instruments in the Radio and Optical

Computational Biology and Applied Bioinformatics

CUDA Application Design and Development

Computational Fluid Dynamics Using Graphics Processing Units: Challenges and Opportunities

GPU Accelerated X-Ray Image Enhancement

Heterogeneous Accelerated Bioinformatics-Perspectives for Cancer Research

The GPU Computing Revolution: From Multi-Core CPUs To Many-Core Graphics Processors

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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