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Vulnerable GPU Memory Management: Towards Recovering Raw Data from GPU

Zhe Zhou, Wenrui Diao, Xiangyu Liu, Zhou Li, Kehuan Zhang, Rui Liu

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Tags: AMD Radeon R7 250, ATI, Cloud, Computer science, nVidia, nVidia GeForce GTX 750, OpenCL, Operating systems, Security

May 26, 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

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

Parallel Wavelet Schemes for Images

David Barina, Michal Kula, Pavel Zemcik

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Tags: AMD Radeon R9 290X, AMD Radeon R9 Fury, ATI, Compression, Discrete Wavelet Transform, Image processing, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX Titan X, OpenCL, Package

May 7, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

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Source codes

Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

A Unified, Hardware-Fitted, Cross-GPU Performance Model

James Stevens, Andreas Klockner

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Tags: AMD Radeon R9 Fury, ATI, Computer science, nVidia, nVidia GeForce GTX Titan X, OpenCL, Performance, Tesla C2070, Tesla K40

April 19, 2016 by hgpu

Efficient Parallel Implementation for Single Block Orthogonal Dictionary Learning

Paul Irofti

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Tags: ATI, ATI FirePro V8800, Computer science, Machine learning, OpenCL

April 12, 2016 by hgpu

Portable and Transparent Software Managed Scheduling on Accelerators for Fair Resource Sharing

Christos Margiolas, Michael F.P. O'Boyle

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Tags: AMD Radeon R9 295X2, ATI, Computer science, nVidia, OpenCL, Performance, Task scheduling, Tesla K20

April 12, 2016 by hgpu

An Exploratory Study of High Performance Graphics Application Programming Interfaces

Joseph Shiraef

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Tags: AMD Radeon R9 290X, ATI, Computer science, DirectX, nVidia, nVidia GeForce GTX 970, OpenGL, Performance, Thesis, Vulkan

April 6, 2016 by hgpu

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Torbjorn Sorman

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Tags: AMD Radeon R7 260X, ATI, Benchmarking, Computer science, DirectCompute, DirectX, nVidia, nVidia GeForce GTX 670, OpenCL, OpenGL, Performance, Thesis

March 22, 2016 by hgpu

Pragma Directed Shared Memory Centric Optimizations on GPUs

Jing Li, Lei Liu, Yuan Wu, Xiang-Hua Liu, Yi Gao, Xiao-Bing Feng, Cheng-Yong Wu

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Tags: ATI, ATI Radeon HD 7850, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenACC, OpenCL, Tesla C2050

March 10, 2016 by hgpu

Hadoop Mapreduce OpenCL Plugin

Vivek Viswanathan

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Tags: AMD Radeon R9 290X, ATI, Computer science, Heterogeneous systems, Java, MapReduce, OpenCL

March 3, 2016 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

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

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

Parallel Wavelet Schemes for Images

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

A Unified, Hardware-Fitted, Cross-GPU Performance Model

Efficient Parallel Implementation for Single Block Orthogonal Dictionary Learning

Portable and Transparent Software Managed Scheduling on Accelerators for Fair Resource Sharing

An Exploratory Study of High Performance Graphics Application Programming Interfaces

Comparison of Technologies for General-Purpose Computing on Graphics Processing Units

Pragma Directed Shared Memory Centric Optimizations on GPUs

Hadoop Mapreduce OpenCL Plugin

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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