Intel and the ISTC for Big Data (2012-2017): A Powerful Collaboration

By Jeff Parkhurst, Ph.D. and Timothy G. Mattson, Ph.D., Intel  The year 2012 was arguably the year that Big Data went mainstream. Data was being hailed as a new class of economic asset, similar to currency or gold, from the … Continue reading

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Decibel: Dataset Branching for Collaborative Data Management

by Michael Maddox, MIT CSAIL, and Aaron J. Elmore, University of Chicago* In Big Data’s wake has come demand for tools to curate, manage and analyze shared datasets collaboratively. For instance, consider researchers in a social media company concurrently working … Continue reading

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Research Updates from the ISTC for Big Data

In August, researchers from Intel and participating institutions gathered at the Intel Science and Technology Center for Big Data’s annual Research Retreat at Intel’s Jones Farm campus in Hillsboro, Oregon to present their latest work and describe their progress. Here … Continue reading

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Fast Data Analysis with SVD

By Jack Dongarra, University of Tennessee Knoxville and Innovative Computing Laboratory The GenBase benchmark was developed as a collaboration with the Intel Parallel Computing Lab, the Broad Institute and Novartis, and the MIT Database Group. Among many challenging tests that the benchmark includes is a computation of the Singular Value … Continue reading

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Improving Query Speeds on Vital Industry Big Data Sets

The Intel Science & Technology Center for Big Data is working on many ways to make it easier to access, store, manage and perform analytics on big, gnarly data sets that are vital to major fields of research. One way … Continue reading

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Benchmarking Graph Databases

ByAlekh Jindal, MIT CSAIL Graph data management has recently received a lot of attention, particularly with the explosion of social media and other complex, inter-dependent datasets. As a result, a number of graph data management systems have been proposed. But … Continue reading

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GenBase: A Benchmark for the Genomics Era

By Rebecca Taft, MIT CSAIL* Genomics is quickly becoming the focus of many Big Data scientists due to the seemingly sudden availability of vast amounts of data.  As mentioned in a previous post, a single gene-sequencing facility can sequence 2000 … Continue reading

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