Explore the words cloud of the ViDaR project. It provides you a very rough idea of what is the project "ViDaR" about.
The following table provides information about the project.
Coordinator |
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Organization address contact info |
Coordinator Country | Switzerland [CH] |
Total cost | 150˙000 € |
EC max contribution | 150˙000 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2017-PoC |
Funding Scheme | ERC-POC |
Starting year | 2018 |
Duration (year-month-day) | from 2018-01-01 to 2019-06-30 |
Take a look of project's partnership.
# | ||||
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1 | ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE | CH (LAUSANNE) | coordinator | 150˙000.00 |
In this project we will build ViDaR, an interface for integrating R with ViDa. R is among the leading data analytics environments (the leading open-source), and is heavily used by data and domain scientists and data analysts in their daily routine. ViDa, developed by an ERC grant, is the state-of-the-art query engine for raw data. It relies on data virtualization, i.e., abstracting data out of its form and manipulating it regardless of the way it is stored or structured, to enable efficient, scalable, querying and manipulation of data in-situ, at their raw format and shape. Integration of ViDa with R will have a positive impact on both systems. For ViDa, it will provide capabilities for data exploration, visualization, mining and analytics, as well as powerful libraries for numerical and statistical computing, thereby substantially growing its user base. For R, it will increase its scale and performance, and reduce the time and effort spent by data scientists on tedious data management tasks. The resulting solution will serve as a proof-of-concept of ViDa’s performance, capabilities, and flexibility for integration with any third-party software that needs to manage vast amounts of raw data.
year | authors and title | journal | last update |
---|---|---|---|
2019 |
Aunn Raza, Periklis Chrysogelos, Panagiotis Sioulas, Vladimir Indjic, Angelos Anadiotis; Anastasia Ailamaki (under submission) GPU-accelerated data management under the test of time published pages: , ISSN: , DOI: |
2019-11-14 | |
2019 |
Periklis Chrysogelos, Manolis Karpathiotakis, Raja Appuswamy, Anastasia Ailamaki HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines. published pages: , ISSN: , DOI: |
2019-11-14 | |
2019 |
Panagiotis Sioulas, Periklis Chrysogelos, Manolis Karpathiotakis, Raja Appuswamy, Anastasia Ailamaki Hardware-conscious Hash-Joins on GPUs published pages: , ISSN: , DOI: |
2019-11-14 | |
2019 |
Periklis Chrysogelos, Panagiotis Sioulas, Anastasia Ailamaki Hardware-conscious Query Processing in GPU-accelerated Analytical Engines published pages: , ISSN: , DOI: |
2019-11-14 |
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The information about "VIDAR" are provided by the European Opendata Portal: CORDIS opendata.
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