Dipartimento di Informatica

The cloud datastores that support today's service economy offer applications the ability to program using a transactional interface. Transactions are groupings of operations that take effect atomically: either all operations take effect or none do. They simplify program development as they allow developers to group related operations into one single atomic unit. For performance, modern datastores allow multiple transactions to execute concurrently. Isolation then defines a contract that regulates the interaction between these concurrent transactions. Indeed, isolation is important also in many machine learning algorithms that iteratively transform some global state, such as model parameters or variable assignment. When these updates are structured as transactions, they can be executed concurrently to achieve greater scalability, relying on isolation to maintain the semantics and theoretical properties of the original serial algorithm.

But what guarantees should isolation offer? And how expensive is it to enforce them?

In my first seminar, I will discuss the fascinating history of our community's attempts at formalizing isolation. You'll meet giants like Jim Gray and Barbara Liskov, Turing award winners who wrestled with this challenge, and you'll see what you think about our recent attempt to venture where such giants have trod.

In the second seminar, I will discuss the tension between providing strong isolation guarantees (which greatly simplify the task of programming concurrent applications) and trying to maximize these applications' performance. Since the elegant foundations of transaction processing were established in the mid 70's with the notion of serializability and the codification of the ACID (Atomicity, Consistency, Isolation, Durability) paradigm, performance has not been considered one of ACID's strong suits, especially for distributed data stores. Indeed, the NoSQL/BASE movement that started a decade ago with Amazon's Dynamo was born out of frustration with the limited scalability of traditional ACID solutions, only to become itself a source of frustration once the challenges of programming applications in this new paradigm began to sink in. But how fundamental is this dichotomy between performance and ease of programming? In my talk, I'll share with you the intellectual journey my students and embarked on trying to overcome the traditional terms of this classic tradeoff.

Lorenzo Alvisi is the Tisch University Professor of Computer Science at Cornell University. Prior to joining Cornell, he held an endowed professorship at UT Austin, where he is now a Distinguished Professor Emeritus. Lorenzo received his Ph.D. in 1996 from Cornell, after earning a Laurea cum Laude in Physics from the University of Bologna. His research interests are in the theory and practice of distributed computing. He is a Fellow of the ACM and IEEE, an Alfred P. Sloan Foundation Fellow, and the recipient of a Humboldt Research Award, an NSF Career Award, and several teaching awards. He serves on the editorial boards of ACM TOCS and Springer's Distributed Computing. In addition to distributed computing, he is passionate about classical music and red Italian motorcycles.