Mixing Consistency in Geodistributed Transactions (Distinguished Lecture)
Andrew Myers,
Cornell University, USA –
Abstract:
Programming concurrent, distributed systems that mutate shared, persistent, geo-replicated state is hard. To enable high availability and scalability, a new class of weakly consistent data stores has become popular. However, some data needs strong consistency. We introduce mixed-consistency transactions, embodied in a new embedded language, MixT. Programmers explicitly associate consistency models with remote storage sites; within each atomic, isolated transaction, data can be accessed with a mixture of different consistency models.
Compile-time information-flow checking, applied to consistency models, ensures that these models are mixed safely and enables the compiler to automatically partition transactions into a single sub-transaction per consistency model. New run-time mechanisms ensure that consistency models can also be mixed safely, even when the data used by a transaction resides on separate, mutually unaware stores. Performance measurements show that despite offering strong guarantees, mixed-consistency transactions can significantly outperform traditional serializable transactions.
Bio
Andrew Myers is a Professor in the Department of Computer Science at Cornell University in Ithaca, NY. He received his Ph.D. in Electrical Engineering and Computer Science from MIT in 1999, advised by Barbara Liskov.
His research interests include computer security, programming languages, and distributed and persistent programming systems. His work on computer security has focused on practical, sound, expressive languages and systems for enforcing information security. The Jif programming language makes it possible to write programs which the compiler ensures are secure, and the Fabric system extends this approach to distributed programming. The Polyglot extensible compiler framework has been widely used for programming language research.
Myers is an ACM Fellow. He has received awards for papers appearing in POPL’99, SOSP’01, SOSP’07, CIDR’13, PLDI’13, and PLDI’15.
Myers is the current Editor-in-Chief for ACM Transactions on Programming Languages and Systems (TOPLAS) and past co-EiC for the Journal of Computer Security. He has also served as program chair or co-chair for a few conferences: ACM POPL 2018, ACM CCS 2016, POST 2014, IEEE CSF 2010, and IEEE S&P 2009.
Host
Rodrigo Seromenho Miragaia Rodrigues
Venue:
Anfiteatro VA4 no piso-1 do Edificio de Civil – IST/Alameda
Upcoming Events
11th Lisbon Machine Learning Summer School

LxMLS 2021 will take place July 7th to July 15th in online format (via zoom and slack). It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), Unbabel and Cleverly.
Click here for information about past editions (LxMLS 2011, LxMLS 2012, LxMLS 2013, LxMLS 2014, LxMLS 2015, LxMLS 2016, LxMLS 2017, LxMLS 2018, LxMLS 2019, LxMLS 2020) and to watch the videos of the lectures (2016, 2017, 2018, 2020).
Call for Participation
Important Dates
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* Application Deadline: May 15, 2021
* Decision: June 1, 2021
* Early Registration: June 15 – July 1, 2021
* Summer School: July 7 – 15, 2021
Topics and Intended Audience
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The school will cover a range of Machine Learning (ML) topics, from theory to practice, that are important in solving Natural Language Processing (NLP) problems that arise in the analysis and use of Web data.
Our target audience is:
- Researchers and graduate students in the fields of NLP and Computational Linguistics;
- Computer scientists who have interests in statistics and machine learning;
- Industry practitioners who desire a more in depth understanding of these subjects.
Features of LxMLS:
- No deep previous knowledge of ML or NLP is required, but the attendants are assumed to have some basic background on mathematics and programming
- Lecturers are leading researchers in machine learning and natural language processing (see speakers)
- Days are divided into morning lectures and afternoon lab sessions and practical talks (see schedule)
- The Labs guide will be provided one month in advance. Last year’s guide can be found here
- A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises
- Both basic (e.g linear classifiers) and advanced topics (e.g. deep learning, reinforcement learning) will be covered
Online Format:
Due to the current COVID-19 pandemic, the 11th Lisbon Machine Learning School will be held online (via zoom and slack). Similar to last year, we are excited for the opportunity to create a virtual school, where you will be able to attend all the lectures, and participate in the Q&As and labs remotely. We will also provide the tools for students to engage with each other remotely. The lectures will also be streamed to YouTube, and will become freely available later in our YouTube channel. The Q&A, labs and social activities will remain restricted to the accepted students only.
List of Confirmed Speakers
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LUIS PEDRO COELHO Fudan University | China
MÁRIO FIGUEIREDO Instituto de Telecomunicações & Instituto Superior Técnico | Portugal
ANDRE MARTINS Instituto de Telecomunicações & Unbabel | Portugal
IRYNA GULEYVICH Technical University Darmstat | Germany
NOAH SMITH University of Washington & Allen Institute for Artificial Intelligence | USA
SLAV PETROV Google Inc. | USA
XAVIER CARRERAS dMetrics | USA
GRAHAM NEUBIG Carnegie Mellon University | USA
BHIKSHA RAJ Carnegie Mellon University | USA
CHRIS DYER Google Deep Mind | UK
ELIAS BARENBOIM Columbia University | USA
ADELE RIBEIRO Columbia University | USA
STEFAN RIEZLER Institut für Computerlinguistik, Universität Heidelberg | Germany
BARBARA PLANK IT University of Copenhagen | Denmark
SASHA RUSH Cornell Tech | USA
Please visit the webpage for up to date information: http://lxmls.it.pt/2021
To apply, please fill the form in https://lisbonmls.wufoo.com/forms/application-form-lxmls-2021/
Any questions should be directed to: lxmls-2021@lx.it.pt.
International European Conference on Parallel and Distributed Computing

The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
Important Dates:
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.