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XLDB 2013 Workshop Europe

28–29 May 2013
CERN
Europe/Zurich timezone

Local Organisers

Session

Lightning Talks on Demand

29 May 2013, 14:00
60/6-015 - Room Georges Charpak (Room F) (CERN)

60/6-015 - Room Georges Charpak (Room F)

CERN

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Conveners

Lightning Talks on Demand

  • Manuel Martin Marquez (CERN)

Presentation materials

There are no materials yet.

  1. 40. All Roads lead to Rome: How Roman Generals would do Large-Scale Machine Learning
    Dr Kostas TZOUMAS
    29/05/2013, 14:00
  2. 41. Collecting use cases
    Mr Jacek Becla
    29/05/2013, 14:05
    XLDB events attempt to expose how different communities manage and analyze their data sets, share lessons learned, pains, find commonalities and more. Due to time constraints the discussions at the XLDB events are only able to scratch the surface. Additionally, it'd be extremely useful to document all the use cases, publicize them, expose to these not present at our events and more....
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  3. 43. Novel Data Compression Methods for Scientific Data
    Dr Shevek
    29/05/2013, 14:10
    A data compression method which is specifically tailored for scientific data can simultaneously tackle the storage, networking and I/O bottlenecks. This talk will introduce three novel techniques for data compression of specific relevance to CERN-style scientific data, and show how the correct choice of data compression technique can even help the scientific method. This is intended to be a...
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  4. 46. Delite: Domain Specific Languages for Big Data and Heterogeneous Parallelism
    Dr Tiark Rompf (Oracle Labs / EPFL)
    29/05/2013, 14:15
    Delite is a compiler framework and runtime for building high-performance DSLs, developed at Stanford and EPFL. Delite DSLs are embedded in Scala to provide a high-level programming model, but generate fast, low-level code for heterogeneous targets using runtime code generation techniques (lightweight modular staging, LMS). With a recently added cluster backend that also includes GPU execution,...
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  5. 31. [DEMO] PostgresRaw
    Dr Miguel Branco (EPFL)
    29/05/2013, 14:20
    As data collections become larger and larger, users are faced with growing bottlenecks in their data analysis. One such bottleneck is the time to prepare and load data into a database system, which is required before any queries can be executed. For many applications, this data-to-query time, i.e. the time between first getting the data and retrieving its first meaningful results, is a crucial...
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