Computing Platforms Seminar Series (COMPASS)

The Computing Platforms Seminar Series (COMPASS) is focused on talks by industry and academia around the general topic of computing platforms.

COMPASS is held on most Thursdays during the semester 10:00-11:00 (with some exceptions) in CAB E 72.

Upcoming Talks:


Friday, 17. May 2019, 12:00-13:00 in CAB E 72

Speaker: Tim Kraska (MIT)

Title: Towards Learned Algorithms, Data Structures, and Systems

 

  

Abstract

All systems and applications are composed from basic data structures and algorithms, such as index structures, priority queues, and sorting algorithms. Most of these primitives have been around since the early beginnings of computer science (CS) and form the basis of every CS intro lecture. Yet, we might soon face an inflection point: recent results show that machine learning has the potential to alter the way those primitives or systems at large are implemented in order to provide optimal performance for specific applications. In this talk, I will provide an overview on how machine learning is changing the way we build systems and outline different ways to build learned algorithms and data structures to achieve “instance-optimality” with a particular focus on data management systems.

Short Bio:

Tim Kraska is an Associate Professor of Electrical Engineering and Computer Science in MIT's Computer Science and Artificial Intelligence Laboratory and co-director of the Data System and AI Lab at MIT (DSAIL@CSAIL). Currently, his research focuses on building systems for machine learning, and using machine learning for systems. Before joining MIT, Tim was an Assistant Professor at Brown, spent time at Google Brain, and was a PostDoc in the AMPLab at UC Berkeley after he got his PhD from ETH Zurich. Tim is a 2017 Alfred P. Sloan Research Fellow in computer science and received several awards including the 2018 VLDB Early Career Research Contribution Award, the 2017 VMware Systems Research Award


 

Past COMPASS Talks:  

Date Speaker Affiliation Talk
25.04.2019 Peter Pietzuch Imperial College London Scaling Deep Learning on Multi-GPU Servers
28.03.2019 Theo Rekatsinas
University of Wisconsin A Machine Learning Perspective on Managing Noisy Data
21.03.2019 Marko Vukolic IBM Research Hyperledger Fabric: a Distributed Operating System for Permissioned Blockchains
28.02.2019 Alberto Lerner University of Fribourg
The Case for Network-Accelerated Query Processing
21.02.2019 Thomas Würthinger Oracle Labs Bringing the Code to the Data with GraalVM
31.01.2019 Irene Zhang Microsoft Research, Redmond Demikernel: An Operating System Architecture for Hardware-Accelerated Datacenter Servers
25.10.2018 Mihnea Andrei SAP HANA Snapshot isolation in HANA - the evolution towards production-grade HTAP
04.10.2018 Philippe Bonnet IT University, Copenhagen, Denmark Near-Data Processing with Open-Channel SSDs
25.09.2018 Nandita Vijaykumar   Carnegie Mellon University Expressive Memory: Rethinking the Hardware-Software Contract with Rich Cross-Layer Abstractions
20.09.2018 Patrick Stüdi IBM Research Data processing at the speed of 100 Gbps using Apache Crail (Incubating)
15.08.2018 Leonid Yavits
Technion Resistive CAM based architectures: Resistive Associative In-Storage Processor and Resistive Address Decoder
06.07.2018 Martin Burtscher Texas State University Automatic Hierarchical Parallelization of Linear Recurrences
15.06.2018 Nitin Agrawal Samsung Research Low-Latency Analytics on Colossal Data Streams with SummaryStore
24.05.2018 Cagri Balkesen Oracle Labs RAPID: In-Memory Analytical Query Processing Engine with Extreme Performance per Watt
16.05.2018 Carsten Binnig TU Darmstadt Towards Interactive Data Exploration
09.05.2018 Bastian Hossbach Oracle Labs Modern programming languages and code generation in the Oracle Database
26.04.2018 Spyros Blanas Ohio State University Scaling database systems to high-performance computers
19.04.2018 Jane Hung MIT The Challenges and Promises of Large-Scale Biological Imaging
12.04.2018 Christoph Hagleitner IBM Research Heterogeneous Computing Systems for Datacenter and HPC Applications
14.03.2018  Eric Sedlar
 Oracle Labs
Why Systems Research Needs Social Science Added to the Computer Science
01.03.2018 Saughata Ghose Carnegie Mellon University How Safe Is Your Storage? A Look at the Reliability and Vulnerability of Modern Solid-State Drives
22.02.2018  Ioannis Koltsidas IBM Research Zurich System software for commodity solid-state storage