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Risk Estimation Without Using Stein’s Lemma — Application to Image Denoising

Sagar Venkatesh Gubbi, Chandra Sekhar Seelamantula

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Tags: ATI, ATI Radeon HD 7950, Computer vision, Image processing, OpenCL, Package, Signal denoising

December 9, 2014 by hgpu

SiftCU: An Accelerated Cuda Based Implementation of SIFT

Mahdi S. Mohammadi, Mehdi Rezaeian

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 440 GT, nVidia GeForce GTX 670, Package

December 2, 2014 by hgpu

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Nam-Luc Tran, Sabri Skhiri, Arnaud Schils, Edgar Isaac Hiroshi Leon Saiki

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan, Package

December 2, 2014 by hgpu

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

Naresh Balaji, Esin Yavuz, Thomas Nowotny

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Tags: Algorithms, Code generation, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GT 755 M, Package

December 2, 2014 by hgpu

Scalable Verification Techniques for Data-Parallel Programs

Nathan Yong Seng Chong

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Tags: ARM, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, OpenCL, Package, Tesla M2050, Thesis

November 25, 2014 by hgpu

Mobile GPGPU Acceleration of Embodied Robot Simulation

Simon Jones, Matthew Studley, Alan Winfield

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Tags: Computer science, OpenCL, Package, Robotics

November 16, 2014 by hgpu

CUDArray: CUDA-based NumPy

Anders Boesen Lindbo Larsen

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Tags: Computer science, CUDA, Neural networks, nVidia, Package, Python

November 16, 2014 by hgpu

Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU

Markus Steinberger, Michael Kenzel, Pedro Boechat, Bernhard Kerbl, Mark Dokter, Dieter Schmalstieg

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Rendering

November 13, 2014 by hgpu

Bounds on the Energy Consumption of Computational Kernels

Andrew Gearhart

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, Package, Tesla K20, Thesis

November 3, 2014 by hgpu

Contract-Based General-Purpose GPU Programming

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package, Software Engineering

October 27, 2014 by hgpu

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 560, Package, Speech recognition

October 22, 2014 by hgpu

A Performance Comparison of Sort and Scan Libraries for GPUs

Bruce Merry

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Tags: Algorithms, AMD Radeon R9 270, ATI, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting, Tesla K40

October 20, 2014 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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high performance computing on graphics processing units: hgpu.org

Packages

Risk Estimation Without Using Stein’s Lemma — Application to Image Denoising

SiftCU: An Accelerated Cuda Based Implementation of SIFT

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

Scalable Verification Techniques for Data-Parallel Programs

Mobile GPGPU Acceleration of Embodied Robot Simulation

CUDArray: CUDA-based NumPy

Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU

Bounds on the Energy Consumption of Computational Kernels

Contract-Based General-Purpose GPU Programming

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

A Performance Comparison of Sort and Scan Libraries for GPUs

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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