Sky Computing
Towards Utility Computing for the Cloud
News
September 25, 2024
Letta, one of UC Berkeley’s most anticipated AI startups, has just come out of stealth
A startup called Letta has just emerged from stealth with tech that helps AI models remember users and conversations. Created in UC Berkeley’s famed labs startup factory, it also announced $10 million in seed money led by Felicis’ Astasia Myers, at a $70 million post-money valuation.
September 11, 2024
Sam Kumar wins 2024 ACM SIGSAC Doctoral Dissertation Runner-up Award
This annual award by SIGSAC recognizes excellent research “for Outstanding PhD Thesis in Computer and Information Security” by doctoral candidates in the field of computer and information security.
September 6, 2024
What AI Is The Best? Chatbot Arena Relies On Millions Of Human Votes
With companies like OpenAI, Google and Meta dropping increasingly sophisticated artificial intelligence products, crowdsourced rankings have emerged as a popular—and virtually only practical—way of determining which tool works best, and LMSYS’s Chatbot Arena has become possibly the most influential real-time gauge.
March 6, 2024
Prof. Natacha Crooks wins IEEE TCDE Rising Star Award
Professor Natacha Crooks awarded the IEEE TCDE Rising Star Award for contributions to distributed data management, and its applications to blockchain technology, security, and cloud computing.
February 20, 2024
Prof. Matei Zaharia and his students and collaborators talk about compound AI systems and their research on them
AI caught everyone’s attention in 2023 with Large Language Models (LLMs) that can be instructed to perform general tasks, such as translation or coding, just by prompting. This naturally led to an intense focus on models as the primary ingredient in AI application development, with everyone wondering what capabilities new LLMs will bring. As more developers begin to build using LLMs, however, we believe that this focus is rapidly changing: state-of-the-art AI results are increasingly obtained by compound systems with multiple components, not just monolithic models.
Events
October 9, 2024
Dr. Kai-Fu Lee (Sinovation Ventures and 01.AI) – Making AI Work: A Roadmap to Unleash the Power of GenAI and Build a Healthier Ecosystem
Generative AI is driving one of the most powerful productivity revolutions in human history, with its rapidly advancing intelligence. However, significant challenges remain before the full potential of large language models (LLMs) can be realized, and a sustainable ecosystem established. Join Dr. Ka…
October 4, 2024
Sky Seminar: Tianyin Xu (UIUC) – Software Reliability in Emerging Cloud Computing Paradigms
Cloud system reliability has been a grand challenge in the past decade due to prevalent, inevitable hardware faults, software bugs, and misconfigurations. Emerging computing paradigms such as microservices, serverless, and sky computing further expand reliability challenges by significantly increasi…
September 27, 2024
Sky Seminar: Ram Alagappan (UIUC) – New Log Abstractions for Datacenter Applications
The log is arguably the simplest yet most pervasive storage abstraction at the heart of many applications. For example, traditional storage-centric applications like databases and key-value stores are built around logs. Similarly, modern applications like stream processing and event sourcing are bui…
September 20, 2024
Sky Seminar: Rebecca Taft (CockroachDB) – CockroachDB: The Resilient Geo-Distributed SQL Database
We live in an increasingly interconnected world, with many organizations operating across countries or even continents. To serve their global user base, organizations are replacing their legacy DBMSs with cloud-based systems capable of scaling OLTP workloads to millions of users. CockroachDB is a sc…
Publications
August 2024
Towards Optimal Transaction Scheduling.
August 2024
Post-Training Sparse Attention with Double Sparsity.
August 2024
The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
August 2024
Compass: Encrypted Semantic Search with High Accuracy.
August 2024
MPC-Minimized Secure LLM Inference.
July 2024
Networks of Networks: Complexity Class Principles Applied to Compound AI Systems Design.
July 2024
Break the Sequential Dependency of LLM Inference Using Lookahead Decoding.
July 2024
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.
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.
Sky Computing Story
Berkeley’s computer science division has an ongoing tradition of 5-year collaborative research labs. Recent labs included the AMPLab (ended in 2016) and the RISELab. These labs have had significant impact in both academia and industry. Past labs publish their research at top conferences in systems, databases, and machine learning. On the industrial side, AMPLab and RISELab fostered several successful startups (Databricks, Opaque, Ponder, Anyscale, to name a few). We are excited to announce the Berkeley Sky Computing Lab where we will strike to make cloud computing a true commodity.
Context
The Sky Computing Lab represents the next chapter of data-intensive systems research at Berkeley. Recent years have seen the explosion of cloud computing. Applications are moving their data and computation to the cloud; on-premise services are dying. In doing so, companies have to make difficult choices between the myriad of cloud providers, each with different services or hardware. Lock-in, whether through artificial migration costs, legal constraints or engineering baggage is real. In the Sky Computing Lab, we will leverage distributed systems, programming languages, security, and machine learning to decouple the services that a company wants to implement from the choice of a specific cloud. Much like the Internet today, cloud computing should be an undifferentiated commodity. Applications should run seamlessly on any or multiple clouds.
Mission
Our mission in the Sky Computing Lab is to transform the cloud into an undifferentiated commodity and ease application burden. As in previous labs, we’re all in — working on everything from basic research to software development, all in the Berkeley tradition of open publication and open source software. Our founding team consists of experts in distributed systems, machine learning, security and programming languages. We’ll use this space to lay out our ideas and progress as we go.
Commitment to Diversity
Sky Computing is guided by Berkeley’s Principles of Community and is committed to providing a safe and caring research environment for every member of our community. We believe that a diverse student body, faculty, and staff are essential to the open exchange of ideas that Sky Computing Lab is founded on.
Our head is in the cloud. We are heading for the SKY.
Sponsors
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