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MNN: A Universal and Efficient Inference Engine

Xiaotang Jiang, Huan Wang, Yiliu Chen, Ziqi Wu, Lichuan Wang, Bin Zou, Yafeng Yang, Zongyang Cui, Yu Cai, Tianhang Yu, Chengfei Lv, Zhihua Wu

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Tags: Computer science, Deep learning, Neural networks, OpenCL, Package, Vulkan

April 12, 2020 by hgpu

Interoperable GPU Kernels as Latency Improver for MEC

Juuso Haavisto, Jukka Riekki

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Tags: Computer science, GLSL, Graphics, nVidia, nVidia GeForce RTX 2080, nVidia Jetson TX2, Package, Vulkan

February 2, 2020 by hgpu

Futhark Vulkan Backend

Steffen Holst Larsen

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Tags: Computer science, nVidia, nVidia GeForce GTX 780 Ti, OpenCL, Package, Vulkan

September 29, 2019 by hgpu

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

Roberto Cavicchioli, Nicola Capodieci, Marco Solieri, Marko Bertogna

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, Package, Vulkan

July 7, 2019 by hgpu

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Grigory Glukhov, Aleksandra Soltan

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Tags: 3D Graphics and Realism, AMD RX Vega 64, ATI, Neural networks, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2070, Thesis, Voxelization, Vulkan

June 23, 2019 by hgpu

Multi-GPU Rendering with Vulkan API

Lars Olav Tolo

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Tags: AMD Radeon RX 460, ATI, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 970, Package, Thesis, Vulkan

May 26, 2019 by hgpu

Vulkan 1.1.97 – A Specification (with all registered Vulkan extensions)

The Khronos Vulkan Working Group

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Tags: Computer science, Vulkan, Whitepaper

January 13, 2019 by hgpu

A Cross-platform Evaluation of Graphics Shader Compiler Optimization

Lewis Crawford, Michael O'Boyle

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Tags: 3D Graphics and Realism, Computer science, Optimization, Performance, Real-time graphics, Shaders, Virtual reality, Vulkan

August 11, 2018 by hgpu

Migrating from OpenGL ES to Vulkan

Imagination Technologies Limited

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

June 28, 2018 by hgpu

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

Loc N. Huynh, Youngki Lee, Rajesh Krishna Balan

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Tags: Algorithms, Computer science, Deep learning, OpenCL, Package, Vulkan

June 25, 2017 by hgpu

Evaluation of Multi-Threading in Vulkan

Axel Blackert

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Tags: AMD Radeon R9 280X, ATI, Computer science, OpenGL, Rendering, Vulkan

January 4, 2017 by hgpu

DeepLearningKit – an GPU Optimized Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

Amund Tveit, Torbjorn Morland, Thomas Brox Rost

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Tags: Computer science, Deep learning, Neural networks, OpenCL, Package, Video, Vulkan

May 17, 2016 by hgpu

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

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

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high performance computing on graphics processing units: hgpu.org

MNN: A Universal and Efficient Inference Engine

Interoperable GPU Kernels as Latency Improver for MEC

Futhark Vulkan Backend

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

GPU Volume Voxelization: Exploration of the performance characteristics of different GPU-based implementations

Multi-GPU Rendering with Vulkan API

Vulkan 1.1.97 – A Specification (with all registered Vulkan extensions)

A Cross-platform Evaluation of Graphics Shader Compiler Optimization

Migrating from OpenGL ES to Vulkan

DeepMon: Mobile GPU-based Deep Learning Framework for Continuous Vision Applications

Evaluation of Multi-Threading in Vulkan

DeepLearningKit – an GPU Optimized Deep Learning Framework for Apple’s iOS, OS X and tvOS developed in Metal and Swift

Recent source codes

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

pplx-garden: Perplexity open source garden for inference technology

LC Framework

OpScanner

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

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