The 1st Workshop on Distributed Infrastructure, Systems, Programming and AI (DISPA)

August 31st, 2020

In conjunction with VLDB 2020

Virtual workshop (on Zoom) - Monday, August 31st, 2020

Twitter: @Dispa2020

Virtual conference registration (free) is available here

Once you've registered for VLDB from here, join DISPA's Zoom events and Slack channel using the links on the VLDB Conferenge Program.

What's new

2020/09/09: Slide for Prof. Shivaram Venkataraman is available at Program page

2020/08/30: Papers and recordings are available at Program page

2020/08/17: Keynote titles and registration link are available.

2020/08/04: Program is available

2020/07/20: Time slots are available at Program page

2020/07/18: Notifications have been sent.

2020/06/12: Updated format (going to virtual)

2020/06/07: Extended the submission deadline (new date is June 20th)

2020/05/31: Keynote speakers are published

2020/05/01: Submission site URL at CMT is added in Call for Papers

2020/04/27: Important dates are updated & programming committee members are added

2020/02/14: Site is created

Overview

The goal of the Distributed Infrastructure Systems, Programming and AI (DISPA) workshop is to bring together researchers and practitioners involved with distributed systems for databases, programmings, and machine learning. Distributed processing has become widespread due to the trend of increasing data volumes, but these research communities remain fairly disjoint. Moreover, industry trends such as public cloud computing are further changing the design of distributed systems, favoring highly elastic and multi-tenant system designs, but there are limited exposures to these challenges in research. We aim to enable an exchange of ideas among researchers and practitioners in this field where we will lead to novel distributed system designs.

There have been many exciting changes in the distributed system fields in recent years, including

  1. the wide adoption of new open source programming tools for massively distributed computation (e.g. PyTorch and Apache Spark)

  2. the rise of public cloud computing, “cloud-native” data management and computation systems such as BigQuery and AWS Aurora

  3. the use of machine learning to manage and optimize distributed systems

  4. new algorithmic advances in deep learning, approximate query processing, information retrieval, and other areas.

This workshop also provides good opportunities to discuss your work to be submitted to Scalable Data Science track at PVLDB.


For any questions regarding the DISPA workshop, please send email to dispa2020-q@googlegroups.com.


Workshop Co-Chairs