Supercharging Big Data Research with New England’s Fastest Supercomputer
An Interview with Jeremy Kepner of MIT Lincoln Laboratory MIT recently announced that the MIT Lincoln Laboratory Supercomputing Center (LLSC) system, housed in Holyoke, Massachusetts, has been ranked the most powerful supercomputer in New England. We caught up with ISTC … Continue reading →
The End of Slow Networks: It’s Time for a Redesign
by Tim Kraska and Carsten Binnig, Brown University Data Management Research Group The next generation of high-performance RDMA-capable networks requires a fundamental rethinking of the design of modern distributed database systems (DDBMS). Current distributed databases are commonly designed under the … Continue reading →
Cutting the Cost and Power Consumption of Big Data Applications, in a Flash
It’s possible to cut the cost and power consumption of Big Data applications by using flash memory as a replacement for conventional RAM, according to new research from ISTC Principal Investigator Arvind and fellow researchers from MIT CSAIL, MIT, and Quanta Research … Continue reading →
Memory Wall? What Memory Wall?
by Holger Pirk, MIT CSAIL* Background With current RAM prices at less than $10K for a Terabyte, in-memory data management is viable, even for “big” data – especially for big data. Given enough Variety and Veracity, however, analyzing a Terabyte of “big” data … Continue reading →
ISTC for Big Data Researchers Present Work at NEDB Day 2015
ISTC for Big Data principal investigators (PIs) and researchers presented a broad base of research work at New England Database Day 2015, which was sponsored by Microsoft and held at the Stata Center at MIT in Cambridge, Mass., on Friday, … Continue reading →
Academic Collaboration: Accelerating the Practical Application of Research
By Jeff Parkhurst, Ph.D., Intel Labs The Intel Science and Technology Center Program is a series of research collaborations that pairs Intel with U.S. universities to identify and prototype revolutionary technology opportunities. The centers are designed to encourage closer collaboration … Continue reading →
Tupleware: An Inside Look
By Eugene Wu, PhD Candidate, MIT CSAIL At the recent ISTC for Big Data annual Research Retreat, Tim Kraska of Brown University presented an in-depth look at Tupleware, an in-memory, read-only distributed computation framework that supports multiple languages. Typical “cloud” … Continue reading →
Scaling Databases to 1000 Cores
By Sungjin Lee, Postdoctoral Associate, Carnegie Mellon University At the Intel Science and Technology Center for Big Data’s annual Research Retreat at Intel’s Jones Farm campus in Hillsboro, Oregon, Xiangyao Yu of MIT described his team’s work in developing solutions … Continue reading →
OLTP Database Systems for Non-Volatile Memory
By Joy Arulraj, Justin Debrabant, Andrew Pavlo, Michael Stonebraker, Stan Zdonik, and Subramanya Dulloor In this joint collaboration between Brown, CMU, MIT CSAIL and Intel Labs, we explore two possible use cases of Non-Volatile Memory (NVM) for on-line transaction processing (OLTP) DBMSs. Evaluation of software systems using NVM is challenging … Continue reading →
Concurrency Control in the Many-core Era: Scalability and Limitations
By Xiangyao Yu, George Bezerra, Michael Stonebraker and Srini Devadas of MIT CSAIL and Andrew Pavlo of Carnegie Mellon University Computers are moving towards an era dominated by many-core machines with dozens or even hundreds of cores on a single chip. This unprecedented … Continue reading →
What’s New
- Intel and the ISTC for Big Data (2012-2017): A Powerful Collaboration
- Solving the “One Concurrency Control Does Not Fit All” Problem for OLTP Databases
- Improving Clinical Decision-Making with Big Data
- ISTC Releases Open Source Code for BigDAWG Polystore System
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