high performance computing on graphics processing units: hgpu.org

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Investigation of heterogeneous computing through novel parallel programming platforms

Andrei-Alexandru Dafinoiu

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Tags: ARM, ATI, ATI Radeon HD 6450, ATI Radeon HD 6570, Computer science, FPGA, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 750 Ti, OpenCL, SoC, Thesis

April 17, 2017 by hgpu

Accelerating High-Throughput Computing through OpenCL

Andrei Dafinoiu, Joshua Higgins, Violeta Holmes

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Tags: ATI, ATI Radeon HD 6570, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 970, OpenCL, Tesla C2050

June 28, 2016 by hgpu

Many-Core Compiler Fuzzing

Christopher Lidbury, Andrei Lascu, Nathan Chong, Alastair F. Donaldson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Compilers, Computer science, FPGA, Intel HD 4600, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenCL, Tesla K40, Tesla M2050

July 10, 2015 by hgpu

GPU concurrency: Weak behaviours and programming assumptions

Jade Alglave, Mark Batty, Alastair F. Donaldson, Ganesh Gopalakrishnan, Jeroen Ketema, Daniel Poetzl, Tyler Sorensen, John Wickerson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Computer science, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 540 M, nVidia GeForce GTX 660, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Tesla C2075

January 21, 2015 by hgpu

Utilizing GPGPU in Computer Emulation

Peter Jakubco, Slavomir Simonak

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Tags: ATI, ATI Radeon HD 6570, Computer science, OpenCL, Package

July 8, 2012 by hgpu

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TorchOpt: an efficient library for differentiable optimization built upon PyTorch

TorchOpt: An Efficient Library for Differentiable Optimization

NaturalCC: An Open-Source Toolkit for Code Intelligence

A Study on Neural-based Code Summarization in Low-resource Settings

mt4g: Memory Topology for GPUs

Capturing the Memory Topology of GPUs

iGniter: an interference-aware GPU resource provisioning framework for achieving predictable performance of DNN inference in the cloud

iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud

pyGSL: A Scalable Library for Graph Structure Learning

pyGSL: A Graph Structure Learning Toolkit

See all packages

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high performance computing on graphics processing units: hgpu.org

Investigation of heterogeneous computing through novel parallel programming platforms

Accelerating High-Throughput Computing through OpenCL

Many-Core Compiler Fuzzing

GPU concurrency: Weak behaviours and programming assumptions

Utilizing GPGPU in Computer Emulation

Recent source codes

SYCL-DNN: a library implementing neural network algorithms written using SYCL

SW#SYCL

StateMover: a checkpoint-based debugging framework for FPGAs

Flink-TornadoVM-Artifact

Kernel Tuner

TorchOpt: an efficient library for differentiable optimization built upon PyTorch

NaturalCC: An Open-Source Toolkit for Code Intelligence

mt4g: Memory Topology for GPUs

iGniter: an interference-aware GPU resource provisioning framework for achieving predictable performance of DNN inference in the cloud

pyGSL: A Scalable Library for Graph Structure Learning

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