SOCK: Serverless-Optimized Containers.
AMBROSIA
Ambrosia is a programming language independent approach for authoring and deploying highly robust distributed applications. Ambrosia dramatically lowers development and deployment costs and time to market by automatically providing recovery and high availability.
Gandiva: Scheduler for DNNs
Gandiva is a cluster scheduling framework that utilizes domain-specific knowledge of deep learning to improve the efficiency of training deep learning models in a GPU cluster.
Astra: Custom-Wired DNNs
Astra is a compilation and execution framework that optimizes execution of a deep learning training job. Instead of treating the computation as a generic data flow graph, Astra exploits domain knowledge about deep learning training…
Instalytics: Storage for Big Data
Instalytics (Intelligent Store-powered Analytics) is a vertically integrated infrastructure stack that enables efficient big data analytics in large-scale data centers, by careful co-design of the storage layer (cluster file system) with the compute layer (query…
Deep Learning Compiler and Optimizer
Project Overview This project aims to build a deep learning compiler and optimizer infrastructure that can provide automatic scalability and efficiency optimization for distributed and local execution. Overall, this stack covers two types of general…