Tag Archives: Compute Architecture

ISTC Researchers Present Work at NEDB Day 2017

ISTC for Big Data principal investigators, researchers and their students presented work at North East Database Day 2017, held at MIT’s Stata Center in Cambridge, Mass., on January 27, 2017. Microsoft and Facebook sponsored the event. The 9th Annual North East … Continue reading

Posted in Big Data Architecture, Data Management, Databases and Analytics, DBMS, ISTC for Big Data Blog, Storage, Streaming Big Data, Visualizing Big Data | Tagged , , , , , , , , , , | Leave a comment

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

Posted in Big Data Architecture, Computer Architecture, High-Performance Computing, ISTC for Big Data Blog, Polystores | Tagged , , , , | Leave a comment

Write-Behind Logging

By Joy Arulraj, Matthew Perron, and Andrew Pavlo, Carnegie Mellon University In a joint collaboration between Carnegie Mellon University and Intel Labs, we explore the changes required in the logging and recovery algorithms in non-volatile memory database management systems (DBMSs). The results of this work … Continue reading

Posted in Big Data Architecture, Data Management, DBMS, ISTC for Big Data Blog, Math and Algorithms, Storage | Tagged , , , , , , , | Leave a comment

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

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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

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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

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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

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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

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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

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A Scalable, Multi-Access Flash Store for Big Data Analytics

Sang Woo Jun, Ming Liu and Arvind, MIT CSAIL Modern data-driven analytics often deal with datasets that do not fit in the main memory of the processing system. In such a scenario, the limiting factor in performance is usually the transportation … Continue reading

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