Data @Scale 2017 Recap
6/15/2017 · Parixit Pol
What this post added
This post recaps the Data @Scale 2017 conference, highlighting discussions on building large-scale storage systems and analytics. Key technical contributions and discussions included: Facebook engineer Pieter Noordhuis's insights on 'Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour' for efficient deep learning at scale; Microsoft's Rimma Nehme discussing the next generation of globally-distributed databases; Alexey Milovidov from Yandex detailing ClickHouse, a DBMS for interactive analytics at scale; Yongsheng Wu from Pinterest sharing insights on the evolution of storage and serving; Maxim Fateev from Uber presenting Cadence, a micro-service architecture beyond request/reply; Kapil Surlaker from LinkedIn explaining UMP and XLNT for reporting and experimentation; Sergey Melnik from Google discussing Spanner's SQL evolution, including distributed query execution and storage formats; Doug Burger from Microsoft on architectures for cloud specialization with programmable hardware; and Steve Stroiney from Facebook describing the system for bulk data movement serving global data storage and processing.