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Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks

Philipp Gysel

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Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla K40, Thesis

May 23, 2016 by hgpu

ImageCL: An Image Processing Language for Performance Portability on Heterogeneous Systems

Thomas L. Falch, Anne C. Elster

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Tags: ATI, ATI Radeon HD 7970, Computer science, Image processing, nVidia, nVidia GeForce GTX 960, OpenCL, Performance, performance portability, Programming Languages, Tesla K40

May 23, 2016 by hgpu

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

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

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high performance computing on graphics processing units: hgpu.org

Applications

Ristretto: Hardware-Oriented Approximation of Convolutional Neural Networks

ImageCL: An Image Processing Language for Performance Portability on Heterogeneous Systems

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

Recent source codes

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

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