Programming

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Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Yani Ioannou, Duncan Robertson, Roberto Cipolla, Antonio Criminisi

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Tags: Computer science, CUDA, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan Z

May 23, 2016 by hgpu

Graphics Supercomputing Applied to Brain Image Analysis with NiftyReg

Francisco Nurudin Alvarez Gonzalez

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Tags: CUDA, Image processing, Image registration, Medicine, nVidia, nVidia GeForce GTX 980, Thesis

May 23, 2016 by hgpu

A Practical Performance Model for Compute and Memory Bound GPU Kernels

Elias Konstantinidis, Yiannis Cotronis

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Tags: Benchmarking, CUDA, OpenCL, Performance prediction

May 23, 2016 by ekondis

The Hitchhiker’s Guide to Cross-Platform OpenCL Application Development

Tyler Sorensen, Alastair F. Donaldson

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Tags: AMD Radeon R7 260, AMD Radeon R9 290X, ATI, Benchmarking, Computer science, Intel HD 5500, nVidia, nVidia GeForce GTX 980, nVidia Quadro K500, OpenCL

May 21, 2016 by hgpu

Architecture-Adaptive Code Variant Tuning

Saurav Muralidharan, Amit Roy, Mary Hall, Michael Garland, Piyush Rai

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Tags: Benchmarking, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 750, nVidia GeForce GTX 770, nVidia GeForce GTX 980, Package, Performance, Tesla C2075, Tesla K20

May 21, 2016 by hgpu

GPU-based Pedestrian Detection for Autonomous Driving

Victor Campmany Canes

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 960, nVidia Tegra TX1, Vehicular traffic

May 21, 2016 by hgpu

Performance Evaluation of Parallel Count Sort using GPU Computing with CUDA

Neetu Faujdar, SatyaPrakash Ghrera

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Sorting

May 21, 2016 by hgpu

Employing Directive Based Compression Solutions on Accelerators Global Memory under OpenACC

Ebad Salehi

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Tags: Compression, Computer science, CUDA, nVidia, OpenACC, OpenCL, Package, Tesla K20, Thesis

May 21, 2016 by hgpu

GPU-Accelerated Feature Tracking

Alex Graves

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 780, OpenCL

May 17, 2016 by hgpu

DeepLearningKit – an GPU Optimized Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

Amund Tveit, Torbjorn Morland, Thomas Brox Rost

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Tags: Computer science, Deep learning, Neural networks, OpenCL, Package, Video, Vulkan

May 17, 2016 by hgpu

A Foray into Efficient Mapping of Algorithms to Hardware Platforms on Heterogeneous Systems

Oren Segal, Nasibeh Nasiri, Martin Margala

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Tags: Benchmarking, Computer science, FPGA, Heterogeneous systems, nVidia, OpenCL, Tesla K40

May 17, 2016 by hgpu

Attention-based NMT Models as Feature Functions in Phrase-based SMT

Marcin Junczys-Dowmunt, Tomasz Dwojak, Rico Sennrich

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Tags: Algorithms, Computer science, CUDA, Machine learning, NLP, nVidia, nVidia GeForce GTX 970

May 17, 2016 by hgpu

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Graphics Supercomputing Applied to Brain Image Analysis with NiftyReg

A Practical Performance Model for Compute and Memory Bound GPU Kernels

The Hitchhiker’s Guide to Cross-Platform OpenCL Application Development

Architecture-Adaptive Code Variant Tuning

GPU-based Pedestrian Detection for Autonomous Driving

Performance Evaluation of Parallel Count Sort using GPU Computing with CUDA

Employing Directive Based Compression Solutions on Accelerators Global Memory under OpenACC

GPU-Accelerated Feature Tracking

DeepLearningKit – an GPU Optimized Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

A Foray into Efficient Mapping of Algorithms to Hardware Platforms on Heterogeneous Systems

Attention-based NMT Models as Feature Functions in Phrase-based SMT

Recent source codes

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

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

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