参考论文Machine Learning in Compiler Optimization I. Introduction It is All About Optimization 编译器有两个任务:translation和optimization。translation是成功将程序翻译成可执行文件。optimization是找到最高效的翻译。 在之前,编译和机器学习是两个不交叠的
The number of optimizations that are available in modern day compilers are in their hundreds, and would only grow in number in the future. This increase in the number of optimizations available to the compiler is primarily due to the fact that each optimization would try and target specific ...
Compiler Auto-Vectorization with Imitation Learning - Charith Mendis, Cambridge Yang, Yewen Pu, Saman P. Amarasinghe, Michael Carbin. NeurIPS 2019. Multi-objective Exploration for Practical Optimization Decisions in Binary Translation - Sunghyun Park, Youfeng Wu, Janghaeng Lee, Amir Aupov, and Scot...
The wealth of available compiler optimizations leads to the dual problems of finding the best set of optimizations and the best heuris-tic parameters to tune each optimization. We describe how machine learning techniques, such as logistic regression, can be used to address these problems. We ...
Navigate to the Machine Learning section and choose Add machine learning resource. On the Create a machine learning resource page, for Resource name, enter resnet50_model. For Model source, choose Use a model stored in S3, such as a model optimized through Deep Learning Compiler. Under S3 ...
in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and...
Compiler and optimizationstacks for deployments on variety of devices. Novel ideas of efficient large-scaledistributed training. inno specific order. This list cares more about overall architectures of AI solutions in production instead of individual machine/deep learning training or inference frameworks. ...
The eIQ Glow neural network compiler software for i.MX RT devices that is found in the MCUXPresso SDK package can be ported to other microcontroller devices in the RT family as well as to some LPC and Kinetis devices. Glow supports compiling machine learning models for Cortex-M4, Cortex-M7,...
In Proceedings of the AAAI Conference on Artificial Intelligence 4780–4789 (AAAI, 2019). Stephenson, M., Amarasinghe, S., Martin, M. & O’Reilly, U.-M. Meta optimization: improving compiler heuristics with machine learning. SIGPLAN Not. 38, 77–90 (2003). Schulte, E., Dorn, J., ...
Alexander Kyte is a software engineer on the Mono compiler team and a published author, who has been following the recent advancements in Machine LearningAnuj is an Architect on the Azure team at Microsoft. A biochemist by trade, technologist by day, and dinner party host by ni...