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A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices

Qiyang Zhang, Xiang Li, Xiangying Che, Xiao Ma, Ao Zhou, Mengwei Xu, Shangguang Wang, Yun Ma, Xuanzhe Liu

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Tags: ARM, Benchmarking, Computer science, Deep learning, OpenCL, OpenGL, Vulkan

February 20, 2022 by hgpu

Analysis of High Level implementations for Recursive Methods on GPUs

Cheng Cao, Justin Kalloor

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Tags: Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 3080, OpenGL, Vulkan

January 9, 2022 by hgpu

Transparent Checkpointing for OpenGL Applications on GPUs

David Hou, Jun Gan, Yue Li, Younes El Idrissi Yazami, Twinkle Jain

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Tags: 3D Graphics and Realism, nVidia, OpenGL, Rendering

March 14, 2021 by hgpu

EasyPBR: A Lightweight Physically-Based Renderer

Radu Alexandru Rosu, Sven Behnke

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Tags: 3D Graphics and Realism, Deep learning, nVidia, nVidia GeForce RTX 2060, OpenGL, Package, Python, Rendering, Visualization

December 13, 2020 by hgpu

AZP: Automatic Specialization for Zero Values in Gaming Applications

Mark W. Stephenson, Ram Rangan

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Tags: Computer science, Games, HLSL, nVidia, nVidia GeForce RTX 2080, OpenGL, Performance, Vulkan

November 29, 2020 by hgpu

A Comparison of Optimal Scanline Voxelization Algorithms

Tim Håkansson

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Tags: 3D Graphics and Realism, CUDA, GLSL, nVidia, OpenGL, Package, Tesla T4, Thesis, Voxelization

September 20, 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

Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

Nadjib Mammeri, Markus Neu, Sohan Lal, Ben Juurlink

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Tags: Computer science, Deep learning, Energy-efficient computing, Heterogeneous systems, Neural networks, OpenCL, OpenGL, SoC

February 23, 2020 by hgpu

On Demand Solid Texture Synthesis Using Deep 3D Networks

Jorge Gutierrez, Julien Rabin, Bruno Galerne, Thomas Hurtut

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Tags: 3D Graphics and Realism, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 2080 Ti, OpenGL, Package, PyTorch

January 19, 2020 by hgpu

Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps

Chaoyang He, Ming Li

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Tags: 3D Graphics and Realism, Algorithms, OpenGL, Rendering

July 7, 2019 by hgpu

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

Harri Renney, Benedict R. Gaster, Tom Mitchell

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Tags: AMD Radeon 530, ATI, FDTD, Finite-difference time-domain, OpenCL, OpenGL, Package, Physics

April 14, 2019 by hgpu

Surface Compression Using Dynamic Color Palettes

Ayub A. Gubran, Felix Huang, Tor M. Aamodt

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Tags: 3D Graphics and Realism, Compression, OpenGL, Rendering

March 24, 2019 by hgpu

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A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

ARMCL-PipeALL: an integrated high-throughput CPU-GPU CNN inference pipeline design for ARM-based Heterogeneous MPSoCs

CPU-GPU Layer-Switched Low Latency CNN Inference

EngineCL for Stratix10 MX

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

Theseus: A Library for Differentiable Nonlinear Optimization

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high performance computing on graphics processing units: hgpu.org

A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices

Analysis of High Level implementations for Recursive Methods on GPUs

Transparent Checkpointing for OpenGL Applications on GPUs

EasyPBR: A Lightweight Physically-Based Renderer

AZP: Automatic Specialization for Zero Values in Gaming Applications

A Comparison of Optimal Scanline Voxelization Algorithms

A Compiler Infrastructure for Embedded Multicore SoCs

Performance Counters based Power Modeling of Mobile GPUs using Deep Learning

On Demand Solid Texture Synthesis Using Deep 3D Networks

Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

Surface Compression Using Dynamic Color Palettes

Recent source codes

A Container-Based Workflow for Distributed Training of Deep Learning Algorithms in HPC Clusters

ARMCL-PipeALL: an integrated high-throughput CPU-GPU CNN inference pipeline design for ARM-based Heterogeneous MPSoCs

EngineCL for Stratix10 MX

Theseus: A Library for Differentiable Nonlinear Optimization

OmpCluster

PipeCNN: An OpenCL-based FPGA Accelerator for Convolutional Neural Networks

hls4ml: Machine learning on FPGAs using HLS

MocCUDA: Prototype to run Pytorch/CUDA on Fugaku

Rodinia Benchmarks for DPC++

DCA++: a state of the art implementation of the dynamical cluster approximation

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