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hgpu.org » Applications » Computer science

VirtCL: a framework for OpenCL device abstraction and management

Yi-Ping You, Hen-Jung Wu, Yeh-Ning Tsai, Yen-Ting Chao

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Tags: Computer science, Heterogeneous systems, Memory model, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Performance

February 23, 2016 by hgpu

Deep Learning At Scale and At Ease

Wei Wang, Gang Chen, Haibo Chen, Tien Tuan Anh Dinh, Jinyang Gao, Beng Chin Ooi, Kian-Lee Tan, Sheng Wang

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 970, Package

February 23, 2016 by hgpu

Sparse Convex Optimization on GPUs

Marco Maggioni

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Sparse matrix, Tesla K40, Thesis

February 23, 2016 by hgpu

Togpu: Automatic Source Transformation from C++ to CUDA using Clang/LLVM

Matthew Marangoni, Thomas Wischgoll

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Tags: Code generation, Computer science, CUDA, Image processing, LLVM, nVidia, Tesla C1060

February 23, 2016 by hgpu

HeSP: a simulation framework for solving the task scheduling-partitioning problem on heterogeneous architectures

Anton Rey, Francisco D. Igual, Manuel Prieto-Matias

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Tags: Algorithms, ARM, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 980, OpenCL, Task scheduling

February 19, 2016 by hgpu

Automatic and portable mapping of data parallel programs to OpenCL for GPU-based heterogeneous systems

Zheng Wang, Dominik Grewe, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, OpenMP, Performance

February 19, 2016 by hgpu

LN-Annote: An Alternative Approach to Information Extraction from Emails using Locally-Customized Named-Entity Recognition

YoungHoon Jung, Karl Stratos, Luca P. Carloni

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Tags: Algorithms, ARM, Cloud, Computer science, Machine learning, Neural networks, NLP, OpenCL

February 19, 2016 by hgpu

Deep Feature-based Face Detection on Mobile Devices

Sayantan Sarkar, Vishal M. Patel, Rama Chellappa

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Tags: Computer science, Computer vision, Deep learning, nVidia, nVidia GeForce GTX 850 M, OpenCL, RenderScript

February 18, 2016 by hgpu

Speeding Up Reinforcement Learning with Graphics Processing Units

Jorn H. Postma

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Tags: Algorithms, Computer science, KD-tree, Machine learning, nVidia, OpenCL, Tesla C2075, Thesis

February 18, 2016 by hgpu

Deep Learning on FPGAs: Past, Present, and Future

Griffin Lacey, Graham W. Taylor, Shawki Areibi

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Machine learning, OpenCL, Overview

February 17, 2016 by hgpu

Finding, Measuring, and Reducing Inefficiencies in Contemporary Computer Systems

Melanie Rae Kambadur

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Tags: Computer science, Intel HD 4600, Intel HD Graphics 4000, LLVM, OpenCL, Package, Performance, Thesis

February 16, 2016 by hgpu

SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures

Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Alexander L. Wolf, Paolo Costa, Peter Pietzuch

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Tags: Computer science, Databases, Heterogeneous systems, nVidia, nVidia Quadro K5200, OpenCL

February 16, 2016 by hgpu

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

An HPC Benchmark Survey and Taxonomy for Characterization

HDM: Home made Diffusion Models

Home-made Diffusion Model from Scratch to Hatch

General Matrix Multiplication (GEMM)

High Performance Matrix Multiplication

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high performance computing on graphics processing units: hgpu.org

Applications

VirtCL: a framework for OpenCL device abstraction and management

Deep Learning At Scale and At Ease

Sparse Convex Optimization on GPUs

Togpu: Automatic Source Transformation from C++ to CUDA using Clang/LLVM

HeSP: a simulation framework for solving the task scheduling-partitioning problem on heterogeneous architectures

Automatic and portable mapping of data parallel programs to OpenCL for GPU-based heterogeneous systems

Deep Feature-based Face Detection on Mobile Devices

Speeding Up Reinforcement Learning with Graphics Processing Units

Deep Learning on FPGAs: Past, Present, and Future

Finding, Measuring, and Reducing Inefficiencies in Contemporary Computer Systems

SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures

Recent source codes

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

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)

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