PaPoC 2022 will take place on April 5th 2022. It is run in hybrid mode with both in-person and remote speakers and attendees. All the times are given in CEST. If speaking or attending remotely, please use time zone converter to find the times in your local time zone.
Opening & Session 1: 08:30 to 09:45
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Making CRDTs Byzantine Fault Tolerant
Martin Kleppmann (University of Cambridge)
08:30, 25m, in-person -
Melda: A General Purpose Delta State JSON CRDT
Amos Brocco (University of Applied Sciences and Arts of Southern Switzerland)
08:55, 25m, in-person -
Relaxed Paxos: Quorum intersection revisited (again)
Heidi Howard (University of Cambridge), Richard Mortier (University of Cambridge)
09:20, 25m, remote
Session 2: 10:30 to 12:10
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Marrying Replicated and Functional Data Structures
Vimala Soundarapandian (IIT Madras), Adharsh Kamath (NITK Surathkal), Kartik Nagar (IIT Madras), KC Sivaramakrishnan (IIT Madras)
10:30, 25m, remote -
Merge What You Can, Fork What You Can’t: Managing Data Integrity in Local-First Software
Nicholas Schiefer (MIT), Geoffrey Litt (MIT), Daniel Jackson (MIT)
10:55, 25m, in-person -
Geo-located data for better dynamic replication
Luis Silva (Universidade Nova de Lisboa), Frederico Aleixo (Universidade Nova de Lisboa), Albert Linde (Universidade Nova de Lisboa), João Leitão (Universidade Nova de Lisboa), Nuno Preguica (Universidade Nova de Lisboa)
11:20, 25m, in-person -
Distributed Access Control for Collaborative Applications using CRDTs
Pierre-Antoine Rault (INRIA), Claudia-Lavinia Ignat (INRIA), Olivier Perrin (Université de Lorraine)
11:45, 25m, in-person
Session 3: 14:00 to 15:40
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An Oblivious Observed-Reset Embeddable Replicated Counter
Matthew Weidner (Carnegie Mellon University), Paulo Sérgio Almeida (HASLab/INESC TEC and Universidade do Minho)
14:00, 25m, remote -
Bilateral Anti-Entropy for Eventual Consistency
Rebecca Bilbro (Rotational Labs), Benjamin Bengfort (Rotational Labs), Pete Keleher (University of Maryland, College Park)
14:25, 25m, remote -
Bolt-On Convergence in Replicated Data Types
Gowtham Kaki (University of Colorado Boulder), Prasanth Prahladan (University of Colorado Boulder), Nicholas Lewchenko (University of Colorado Boulder)
14:50, 25m, remote -
Ordering Operations for Generic Replicated Data Types using Version Trees
Nazmus Saquib (University of California, Santa Barbara), Chandra Krintz (University of California, Santa Barbara), Rich Wolski (University of California, Santa Barbara)
15:15, 25m, remote
Session 4: 16:30 to 18:30
Invited Talk 1: Implementing Distributed ACID Transactions Without Atomic Clocks
Karthik Ranganathan, CTO, YugaByte
16:30, 60m, remote
Abstract
ACID transactions are a fundamental building block when developing business-critical, user-facing applications. They simplify the complex task of ensuring data integrity while supporting highly concurrent operations. While they are taken for granted in monolithic SQL databases, most distributed DBs would forsake them completely.
Fortunately, this is no longer the case. The trend started with Google Spanner, which offered distributed transactions using GPS based atomic clocks - unheard of in the database world before. Now, distributed transactions - without requiring atomic clocks - are offered by distributed SQL databases. One such example of a fully open source database offering this is YugabyteDB. Using the example of YugabyteDB, this talk will explain how distributed ACID transactions can be achieved without atomic clocks - without compromising on performance.
Bio
Karthik was one of the original database engineers at Facebook responsible for building distributed databases including Cassandra and HBase. He is an Apache HBase committer, and also an early contributor to Cassandra, before it was open-sourced by Facebook. He is currently the co-founder and CTO of the company behind YugabyteDB, a fully open-source distributed SQL database for building cloud-native and geo-distributed applications.
Invited Talk 2: A Programmable Cloud: CALM Foundations and Open Challenges
Joseph M. Hellerstein, Professor, UC Berkeley
17:30, 60m, remote
Abstract
The public cloud emerged a decade ago, yet distributed systems are still programmed using models from sequential computing. All the traditional challenges of distributed programming and data are still present in the cloud, only they are now faced by the general population of software developers. Added to these challenges are new desires for “serverless” computing, including consumption-based pricing and autoscaling.
This talk will highlight principles for cloud programming that I have explored with colleagues over the past decade, including the CALM Theorem and languages like Dedalus and Bloom that encourage monotonic coordination-free consistency via logic and lattices. The Anna “any-scale” KVS will be presented as a petri dish for the potential of these ideas and many remaining challenges.
I will conclude by overviewing new work in the Hydro project, which is aimed at bringing research ideas to programmers in an practical, evolutionary fashion. Key to our approach is a separation of distributed programs into a PACT of four facets: Program semantics, Availablity, Consistency and Trust. We propose to migrate developers gradually to PACT programming by lifting familiar code into our more declarative level of abstraction. This agenda raises challenges across multiple areas including language design, query optimization, transactions, distributed consistency, compilers and program synthesis.
Bio
Joe Hellerstein is the Jim Gray Professor of Computer Science at the University of California, Berkeley. His research focuses on data-centric systems and the way they drive computing. Hellerstein is an ACM Fellow, a Sloan Research Fellow and the recipient of three ACM-SIGMOD Test of Time awards. In 2010, MIT’s Technology Review magazine included his work on cloud programming in their TR10 list of the 10 technologies “most likely to change our world”. In addition to his academic work, Hellerstein has been involved in a number of startup companies including Trifacta, which brought academic research on data wrangling to market.