Sky Computing

Ion Stoica – Featured Projects

SkyPilot

To comply with the increasing number of government regulations about data placement and processing, and to protect themselves against major cloud outages, many users want the ability to easily migrate their workloads between clouds. We propose doing so not by imposing uniform and comprehensive standards, but by creating a fine-grained two-sided market via intercloud brokers. SkyPilot is an intercloud broker that treats the cloud ecosystem not just as a collection of individual and largely incompatible clouds but as a more integrated Sky of Computing. SkyPilot enables users to run Machine Learning and Data Science batch jobs seamlessly on any cloud, reduce cloud costs substantially, tap into best-in-class hardware on different clouds, and enjoy higher resource availability.

Skyplane

Cloud applications are increasingly distributing data across multiple regions and cloud providers in response to privacy regulations, to take advantage of specialized hardware, and to prevent vendor lock-in. Unfortunately, wide-area bulk data transfers are often slow and expensive due to egress fees. This work aims to reduce both the latency and the cost of inter-cloud bulk transfer by using a variety of techniques, including overlay routing, multiple instances, multiple TCP connections, and taking advantage of different network tiers. Together, these techniques allow Skyplane to significantly improve object transfer throughput and lower the costs.

Natacha Crooks – Featured Project

Basil

Basil explores the design of SQL databases with high integrity and decentralized trust. How can traditional functionality like ACID transactions and SQL queries be efficiently implemented when trust is decentralized among n distinct parties, of which a subject can misbehave.

Joseph Gonzalez – Featured Project

Gorilla

The Gorilla project is designed to connect large language models (LLMs) with a wide range of services and applications exposed through APIs. Imagine if ChatGPT could interact with thousands of services, ranging from Instagram and Doordash to tools like Google Calendar and Stripe, to help you accomplish tasks. This may be how we interact with computers and even the web in the future. Gorilla is an LLM that we train using a concept we call retriever-aware training (RAT), which picks the right API to perform a task that a user can specify in natural language. Gorilla also introduces an Abstract Syntax Tree (AST) based sub-tree matching algorithm, which for the first time allows us to measure hallucination of LLMs!

Raluca Ada Popa – Featured Project

MC²

MC² is a platform for running secure analytics and machine learning on encrypted data. With MC², organizations can safely upload their confidential data to the cloud in encrypted form and securely compute analytics and machine learning without exposing the unencrypted data to the cloud provider. MC² also enables secure collaboration among multiple organizations, where the data owners can use the platform to jointly analyze their collective data without revealing their individual data to each other.

Koushik Sen – Featured Project

FuzzFactory

FuzzFactory is domain-specific fuzz testing tool that generalizes coverage-guided fuzzing to domain-specific testing goals. FuzzFactory allows users to guide the fuzzer’s search process without having to modify the core search algorithm.