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Understanding the impact of CUDA tuning techniques for Fermi

Yuri Torres, Arturo Gonzalez-Escribano, Diego R. Llanos

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

November 10, 2011 by hgpu

Exploring Applications in CUDA

Michael Kubacki

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Tags: Computer science, CUDA, nVidia

November 10, 2011 by hgpu

A CPU-GPU Hybrid Runtime for the Aeminium Language

Alcides Fonseca

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Source codes

Tags: Compilers, Computer science, Java, MapReduce, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Package, Sorting, Thesis

November 10, 2011 by hgpu

GrAVity: a massively parallel antivirus engine

Giorgos Vasiliadis, Sotiris Ioannidis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Security

November 9, 2011 by hgpu

Parallel Implementation of Otsu’s Binarization Approach on GPU

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Parallel Implementation of Souvola’s Binarization Approach on GPU

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Low Complexity Corner Detector Using CUDA for Multimedia Applications

Rajat Phull, Pradip Mainali, Qiong Yang, Patrice Rondao Alface, Henk Sips

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 280

November 9, 2011 by hgpu

Effects of GPU and CPU Loads on Performance of CUDA Applications

Maksim Bobrov, Roy Melton, Stanislaw Radziszowski, Marcin Lukowiak

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Tags: AES, Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 285, Performance, Security

November 9, 2011 by hgpu

Large data visualization on distributed memory multi-GPU clusters

Thomas Fogal, Hank Childs, Siddharth Shankar, Jens Kruger, R. Daniel Bergeron, Philip Hatcher

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Tags: Algorithms, Computer science, GLSL, GPU cluster, nVidia, nVidia GeForce 8800 GTX, nVidia Quadro FX 5800, OpenGL, Performance, Rendering, Visualization

November 9, 2011 by hgpu

Automatic transformation and optimization of applications on GPUs and GPU clusters

Wenjing Ma

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Tags: Algorithm optimization, Algorithms, Benchmarking, Code generation, Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2, Optimization, Tesla T10, Thesis

November 9, 2011 by hgpu

GPU-based ray casting of stacked out-of-core height fields

Christopher Lux, Bernd Frohlich

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Tags: Computer science, GLSL, nVidia, nVidia GeForce GTX 480, OpenCL, OpenGL, Rendering, Visualization

November 9, 2011 by hgpu

Parallel Implementation of Niblack’s Binarization Approach on CUDA

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 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

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

Understanding the impact of CUDA tuning techniques for Fermi

Exploring Applications in CUDA

A CPU-GPU Hybrid Runtime for the Aeminium Language

GrAVity: a massively parallel antivirus engine

Parallel Implementation of Otsu’s Binarization Approach on GPU

Parallel Implementation of Souvola’s Binarization Approach on GPU

Low Complexity Corner Detector Using CUDA for Multimedia Applications

Effects of GPU and CPU Loads on Performance of CUDA Applications

Large data visualization on distributed memory multi-GPU clusters

Automatic transformation and optimization of applications on GPUs and GPU clusters

GPU-based ray casting of stacked out-of-core height fields

Parallel Implementation of Niblack’s Binarization Approach on CUDA

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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