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Romou: Rapidly Generate High-Performance Tensor Kernels for Mobile GPUs

Rendong Liang, Ting Cao, Jicheng Wen, Manni Wang, Yang Wang, Jianhua Zou, Yunxin Liu

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Tags: Code generation, Computer science, OpenCL, Package, Performance, Vulkan

March 6, 2022 by hgpu

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

Shenggan Cheng, Ruidong Wu, Zhongming Yu, Binrui Li, Xiwen Zhang, Jian Peng, Yang You

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Tags: Biology, Computer science, CUDA, Machine learning, nVidia, nVidia A100, Package

March 6, 2022 by hgpu

Query Processing on Tensor Computation Runtimes

Dong He, Supun Nakandala, Dalitso Banda, Rathijit Sen, Karla Saur, Kwanghyun Park, Carlo Curino, Jesús Camacho-Rodríguez, Konstantinos Karanasos, Matteo Interlandi

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Tags: Benchmarking, Cloud, Computer science, CUDA, Databases, Machine learning, nVidia, Package, Tesla P100

March 6, 2022 by hgpu

Enabling On-Device Smartphone GPU based Training: Lessons Learned

Anish Das, Young D. Kwon, Jagmohan Chauhan, Cecilia Mascolo

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

March 6, 2022 by hgpu

A ML-based resource utilization OpenCL GPU-kernel fusion model

Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava

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Tags: Computer science, Data parallelism, HPC, Machine learning, nVidia, nVidia GeForce GT 740 M, nVidia GeForce GTX 760, OpenCL

February 20, 2022 by hgpu

Lightning: Scaling the GPU Programming Model Beyond a Single GPU

Stijn Heldens, Pieter Hijma, Ben van Werkhoven, Jason Maassen, Rob V. van Nieuwpoort

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Tags: Computer science, CUDA, Distributed computing, nVidia, OpenCL, Package, Performance, Tesla P100

February 20, 2022 by hgpu

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

Electrical-Level Attacks on CPUs, FPGAs, and GPUs: Survey and Implications in the Heterogeneous Era

Dina G. Mahmoud, Vincent Lenders, Mirjana Stojilović

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Tags: Computer science, FPGA, Heterogeneous systems, Security, survey

February 13, 2022 by hgpu

Pattern-based Programming Abstractions for Heterogeneous Parallel Computing

August Ernstsson

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Tags: Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, OpenCL, Tesla K20, Thesis

February 13, 2022 by hgpu

The Ecological Footprint of Neural Machine Translation Systems

Dimitar Sherionov, Eva Vanmassenhove

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, LSTM, NLP, nVidia, nVidia GeForce GTX 1080 Ti, Package, Tesla P100

February 13, 2022 by hgpu

Improving Loop Parallelization by a Combination of Static and Dynamic Analyses in HLS

Florian Dewald, Johanna Rohde, Christian Hochberger, Heiko Mantel

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Tags: Computer science, FPGA, HLS, Package

February 13, 2022 by hgpu

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Nick Iliev, Amit R Trivedi

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Tags: CNN, Computer science, Deep learning, FPGA, Matrix decomposition, Neural networks, nVidia, nVidia Jetson AGX Xavier, Performance

February 13, 2022 by hgpu

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Romou: Rapidly Generate High-Performance Tensor Kernels for Mobile GPUs

FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours

Enabling On-Device Smartphone GPU based Training: Lessons Learned

A ML-based resource utilization OpenCL GPU-kernel fusion model

Lightning: Scaling the GPU Programming Model Beyond a Single GPU

A Comprehensive Benchmark of Deep Learning Libraries on Mobile Devices

Electrical-Level Attacks on CPUs, FPGAs, and GPUs: Survey and Implications in the Heterogeneous Era

Pattern-based Programming Abstractions for Heterogeneous Parallel Computing

The Ecological Footprint of Neural Machine Translation Systems

Improving Loop Parallelization by a Combination of Static and Dynamic Analyses in HLS

FC_ACCEL: Enabling Efficient, Low-Latency and Flexible Inference in DNN Fully Connected Layers, using Optimized Checkerboard Block matrix decomposition, fast scheduling, and a resource efficient 1D PE array with a custom HBM2 memory subsystem

Recent source codes

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

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