high performance computing on graphics processing units: hgpu.org

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A Framework for Automated Generation of Specialized Function Variants

Nicholas Chaimov

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Tags: Cloud, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, Optimization, Tesla C2070, Tesla S1070, Thesis

November 6, 2012 by hgpu

All-Pairs Shortest Path Algorithms Using CUDA

Jeremy Mark Kemp

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 470, Path problems, Thesis

November 6, 2012 by hgpu

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

Shane Cook

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Tags: Book, Computer science, CUDA, nVidia, Tutorial

November 5, 2012 by hgpu

Load-Balanced Multi-GPU Ambient Occlusion for Direct Volume Rendering

Alexandre Ancel, Jean-Michel Dischler, Catherine Mongenet

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Tags: Algorithms, Computer science, CUDA, Interactive application, nVidia, nVidia GeForce GTX 295, OpenMP, Rendering, Tesla C2050, Visualization

November 5, 2012 by hgpu

cphVB: A System for Automated Runtime Optimization and Parallelization of Vectorized Applications

Mads Ruben Burgdorff Kristensen, Simon Andreas Frimann Lund, Troels Blum, Brian Vinter

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Tags: Computer science, OpenCL, Optimization, Package, Programming Languages, Python

November 5, 2012 by hgpu

Kite: Braided Parallelism for Heterogeneous Systems

J. Garrett Morris, Benedict R. Gaster, Lee Howes

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Tags: Compilers, Computer science, Heterogeneous systems, OpenCL, Programming techniques

November 5, 2012 by hgpu

DL: A data layout transformation system for heterogeneous computing

I-Jui Sung, Geng Daniel Liu, Wen-Mei W. Hwu

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Package

November 1, 2012 by hgpu

An Intermediate Library for Multi-GPUs Computing Skeletons

Le Duc Tung, Nguyen Huu Duc, Pham Tuan Anh, Ngo Huy Hoang, Nguyen Minh Thap

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Tags: Code generation, Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 295

November 1, 2012 by hgpu

Efficient Pattern-Based Time Series Classification on GPU

Kai-Wei Chang, Biplab Deka, Wen-Mei W. Hwu, Dan Roth

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480

October 31, 2012 by hgpu

Parallel Genetic Programming on Graphics Processing Units

Douglas A. Augusto, Heder S. Bernardino, Helio J.C. Barbosa

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Tags: Algorithms, Computer science, Genetic programming, OpenCL, Optimization, Review

October 31, 2012 by hgpu

Impact of GPU Memory Access Patterns on FDTD

Matthew Livesey, James F. Stack Jr., Fumie Costenz, Takeshi Nanri, Norimasa Nakashima, Seiji Fujino

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Tags: Computer science, CUDA, FDTD, Finite-difference time-domain, nVidia, Performance, Tesla M2050

October 30, 2012 by hgpu

Characterization and Exploitation of GPU Memory Systems

Kenneth Sydney Lee

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Tags: AMD Fusion, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computer science, Memory model, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla C2075, Thesis

October 30, 2012 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

BoltzGen:Toward Universal Binder Design

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

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

All-Pairs Shortest Path Algorithms Using CUDA

CUDA Programming: A Developer’s Guide to Parallel Computing with GPUs

Load-Balanced Multi-GPU Ambient Occlusion for Direct Volume Rendering

cphVB: A System for Automated Runtime Optimization and Parallelization of Vectorized Applications

Kite: Braided Parallelism for Heterogeneous Systems

DL: A data layout transformation system for heterogeneous computing

An Intermediate Library for Multi-GPUs Computing Skeletons

Efficient Pattern-Based Time Series Classification on GPU

Parallel Genetic Programming on Graphics Processing Units

Impact of GPU Memory Access Patterns on FDTD

Characterization and Exploitation of GPU Memory Systems

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

BoltzGen:Toward Universal Binder Design

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

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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