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Intel S&TC for Big Data
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The Intel Science & Technology Center for Big Data (located at MIT CSAIL)
The Intel Science & Technology Center for Big Data (located at MIT CSAIL)

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The Intel Science & Technology Center for Big Data was a five-year, Intel-backed academic-industry research initiative to discover new Big Data infrastructure technologies. It ran from September 2012 to August 2017. It brought together some of the leading minds working in database technology today, from eight top universities and +Intel Labs.

Read what the ISTC accomplished in this blog post by co-directors Michael Stonebraker (2014 Turing Award winner) and +Sam Madden of +CSAIL MIT with +Timothy G Mattson of Intel Labs.

A full history of the project is available at http://istc-bigdata.org/#&panel1-2 including links to open-source software produced by the ISTC.
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This week at VLDB 2017, Intel S&TC PI Arvind and colleagues at +CSAIL MIT presented a new system for data center caching that uses flash memory, the kind of memory used in most smartphones, to make data centers operate more efficiently.
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Congrats to ISTC technical advisor Pradeep Dubey and Intel researchers Nadathur Satish and Narayanan Sundaram on their paper "Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data.. It describes what the authors believe to be the most scalable deep-learning implementation in the world currently, and runs on Intel Xeon Phi technology.

The work involved a collaboration between Intel, the National Energy Research Scientific Computing Center, and Stanford.

Read the article on HPCWire
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At the VLDB 2017 Conference on Monday, August 28, the intriguingly titled FADS Workshop (Failed Aspirations in Database Systems) looks back at promising ideas in database systems technology that, for whatever reason, just didn't go - and possible lessons-learned for computer scientists & researchers.

Impressive line-up, including Phil Bernstein of Microsoft Research and Professor Margo Seltzer of Harvard University (Berkeley DB/ Sleepycat Software). ISTC PI Andy Pavlo of Carnegie Mellon University is workshop chair.

Here's the full program line-up (10:30 - 17:00): http://fads.ws/program/
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Intel S&TC researchers at Portland State University and University of Washington have been on the cutting edge of the Smart Cities movement in the Northwest, innovating in urban analytics and advocating for open data and responsible algorithmic decision making.

"+Bill Howe, associate director of the eScience Institute at the UW, said the region can lead with policies that ensure 'responsible algorithmic decision making,' or data-driven models that take into account human observation. He called it a “huge opportunity.”

Read PSU Professor (and Smart Cities activist) +Kristin Tufte's most recent blog post on how urban analytics can enable Smart Cities through improved transportation. http://istc-bigdata.org/…/urban-analytics-for-smart-cities…/
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Breakthrough Intel S&TC-backed research from +CSAIL MIT's Peter Szolovits, PhD students & colleagues: using machine learning to overcome the Big Data variety problem in critical care.

The "ICU Intervene" approach uses ML to create predictive models from large amounts of past ICU data, which could help doctors make informed decisions in time-pressed and stressful critical-care environments.

"EHR Model Transfer" works across different EHR platforms, using natural language processing to analyze and relate data from different hospitals - which could shave time and error from clinical decision-making.
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With all the dramatic improvements happening in hardware (memory, storage, networks), what will the future of databases look like? Who better to ask than Mike Stonebraker, pioneer and prolific serial entrepreneur in database technology (and recipient of the 2014 Turing Award for his vast contributions).

How have his beliefs changed (or not) over his 40+ years in this sector? Great, wide-ranging Q&A article.
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As the Intel Science & Technology Center for Big Data winds to its close (September 2012-August 2017), co-founders Michael Stonebraker and +Sam Madden (of +CSAIL MIT) and +Intel lead +Timothy G Mattson look back on all that it achieved.
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Performing analytics inside databases is progressively more important. Case in point: array data. But it becomes increasingly difficult as data volumes start to outstrip the capabilities of traditional data stores.

Intel S&TC Principal Investigator +Jack Dongarra, +Piotr Luszczek and Thomas Herault of the University of Tennessee, Knoxville show how in-database analytics can address this problem directly with the use of modern database systems (like SciDB) and established numerical algorithms.
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