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

Yang He

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Tags: Computer science, CUDA, Deep learning, nVidia, PyTorch, Software Engineering, Tesla V100, Thesis

November 13, 2022 by hgpu

Long Code for Code Search

Fan Hu, Yanlin Wang, Lun Du, Hongyu Zhang, Shi Han, Dongmei Zhang, Xirong Li

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Tags: Computer science, Deep learning, NLP, nVidia, Software Engineering, Tesla V100

August 28, 2022 by hgpu

Manas: Mining Software Repositories to Assist AutoML

Giang Nguyen, Johir Islam, Rangeet Pan, Hridesh Rajan

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Tags: Computer science, Deep learning, Neural networks, nVidia, Package, Python, Software Engineering, Tesla V100

December 12, 2021 by hgpu

GPURepair: Automated Repair of GPU Kernels

Saurabh Joshi, Gautam Muduganti

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Tags: Computer science, CUDA, OpenCL, Package, Software Engineering

November 22, 2020 by hgpu

A Compiler Infrastructure for Embedded Multicore SoCs

Weihua Sheng

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Tags: Benchmarking, Compilers, Computer science, GLSL, OpenGL, SoC, Software Engineering, Thesis

June 14, 2020 by hgpu

Lessons learned in a decade of research software engineering GPU applications

Ben van Werkhoven, Willem Jan Palenstijn, Alessio Sclocco

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Tags: Computer science, CUDA, nVidia, OpenCL, Software Engineering

May 31, 2020 by hgpu

hlslib: Software Engineering for Hardware Design

Johannes de Fine Licht, Torsten Hoefler

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Tags: Computer science, FPGA, OpenCL, Package, Software Engineering

October 13, 2019 by hgpu

Charactering and Detecting CUDA Program Bugs

Mingyuan Wu, Husheng Zhou, Lingming Zhang, Cong Liu, Yuqun Zhang

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Tags: Computer science, CUDA, LLVM, nVidia, Package, Software Engineering

May 8, 2019 by hgpu

DLL: A Blazing Fast Deep Neural Network Library

Baptiste Wicht, Jean Hennebert, Andreas Fischer

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 960, Package, Software Engineering

April 15, 2018 by hgpu

Implementing and Evaluating Candidate-Based Invariant Generation

Adam Betts, Nathan Chong, Pantazis Deligiannis, Alastair F. Donaldson, Jeroen Ketema

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Software Engineering

December 10, 2016 by hgpu

Integrating a large-scale testing campaign in the CK framework

Andrei Lascu, Alastair F. Donaldson

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Tags: Computer science, OpenCL, Software Engineering

November 11, 2015 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

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KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

Three Contributions to the Theory and Practice of Optimizing Compilers

HETU: a high-performance distributed deep learning system targeting large-scale and automated distributed training

Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism

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

See all packages

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high performance computing on graphics processing units: hgpu.org

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

Long Code for Code Search

Manas: Mining Software Repositories to Assist AutoML

GPURepair: Automated Repair of GPU Kernels

A Compiler Infrastructure for Embedded Multicore SoCs

Lessons learned in a decade of research software engineering GPU applications

hlslib: Software Engineering for Hardware Design

Charactering and Detecting CUDA Program Bugs

DLL: A Blazing Fast Deep Neural Network Library

Implementing and Evaluating Candidate-Based Invariant Generation

Integrating a large-scale testing campaign in the CK framework

Contract-Based General-Purpose GPU Programming

Recent source codes

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

HETU: a high-performance distributed deep learning system targeting large-scale and automated distributed training

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

SW#SYCL

Flink-TornadoVM-Artifact

StateMover: a checkpoint-based debugging framework for FPGAs

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

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