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E2DATA SIGNED

European Extreme Performing Big Data Stacks

Total Cost €

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EC-Contrib. €

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Partnership

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Project "E2DATA" data sheet

The following table provides information about the project.

Coordinator
EXUS SOFTWARE LTD 

Organization address
address: OLD BROAD STREET 25 TOWER 42
city: LONDON
postcode: EC2N 1PB
website: www.exus.co.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 4˙676˙250 €
 EC max contribution 4˙676˙250 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2017-1
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-01-01   to  2020-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    EXUS SOFTWARE LTD UK (LONDON) coordinator 503˙125.00
2    DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH DE (KAISERSLAUTERN) participant 720˙750.00
3    THE UNIVERSITY OF MANCHESTER UK (MANCHESTER) participant 658˙750.00
4    BAMBOO SYSTEMS GROUP LIMITED UK (CAMBRIDGE) participant 610˙750.00
5    INSTITUTE OF COMMUNICATION AND COMPUTER SYSTEMS EL (ATHINA) participant 590˙750.00
6    NEUROCOM LUXEMBOURG SA LU (LUXEMBOURG) participant 505˙625.00
7    IPROOV LIMITED UK (LONDON) participant 483˙625.00
8    SPARK WORKS ITC UK (SWADLINCOTE DERBYSHIRE) participant 315˙375.00
9    INSTITOUTO TECHNOLOGIAS YPOLOGISTONKAI EKDOSEON DIOFANTOS EL (PATRAS) participant 287˙500.00

Map

 Project objective

Imagine a Big Data application with the following characteristics: (i) it has to process large amounts of complex streaming data, (ii) the application logic that processes the incoming data must execute and complete within a strict time limit, and (iii) there is a limited budget for infrastructure resources.

In today’s world, the data would be streamed from the local network or edge devices to a cloud provider which is rented by a customer to perform the data execution. The Big Data software stack, in an application and hardware agnostic manner, will split the execution stream into multiple tasks and send them for processing on the nodes the customer has paid for. If the outcome does not match the strict three second business requirement, then the customer has two options: 1) scale-up (by upgrading processors at node level), 2) scale-out (by adding nodes to their clusters), or 3) manually implement code optimizations specific to the underlying hardware.

E2Data proposes an end-to-end solution for Big Data deployments that will fully exploit and advance the state-of-the-art in infrastructure services by delivering a performance increase of up to 10x while utilizing up to 50% less cloud resources. E2Data will provide a new Big Data paradigm, by combining state-of-the-art software components, in order to achieve maximum resource utilization for heterogeneous cloud deployments without affecting current programming norms (i.e. no code changes in the original source). The E2Data innovations will be driven by the requirements of four resource demanding applications from the finance, health, green buildings, and security domains. Finally, the evaluation will be conducted on both high-performing x86 and low-power ARM cluster architectures representing realistic execution scenarios of real-world deployments.

 Deliverables

List of deliverables.
Prototype V1 and preliminary evaluation Documents, reports 2020-03-04 09:44:22
Project Presentation and web portal Other 2020-03-04 09:44:22
The Intelligent Scheduler Definition Documents, reports 2020-03-04 09:44:22
Quality plan Documents, reports 2020-03-04 09:44:22
Intermediate API definition Documents, reports 2020-03-04 09:44:22
E2Data architecture Documents, reports 2020-03-04 09:44:22
Dissemination and exploitation activities report 1 Documents, reports 2020-03-04 09:44:22
User requirements and data management plan Documents, reports 2020-03-04 09:44:22

Take a look to the deliverables list in detail:  detailed list of E2DATA deliverables.

 Publications

year authors and title journal last update
List of publications.
2019 Traub, Jonas; Grulich, Philipp; Cuéllar, Alejandro Rodríguez; Breß, Sebastian; Katsifodimos, Asterios; Rabl, Tilmann; Markl, Volker
Efficient window aggregation with general stream slicing
published pages: , ISSN: , DOI: 10.5441/002/edbt.2019.10
22nd International Conference on Extending Database Technology 2019 March 2020-03-04
2019 Breß, S., Funke, H., Zeuch, S., Rabl, T. & Markl, V.
An Overview of Hawk: A Hardware-Tailored Code Generator for the Heterogeneous Many Core Age
published pages: , ISSN: , DOI: 10.18420/btw2019-ws-07
BTW 2019 – Workshopband. 2020-03-04
2018 Clemens Lutz, Sebastian Breß, Tilmann Rabl, Steffen Zeuch, Volker Markl
Efficient and Scalable k‑Means on GPUs
published pages: 157-169, ISSN: 1618-2162, DOI: 10.1007/s13222-018-0293-x
Datenbank-Spektrum 18/3 2020-03-04
2018 Sebastian Breß, Bastian Köcher, Henning Funke, Steffen Zeuch, Tilmann Rabl, Volker Markl
Generating custom code for efficient query execution on heterogeneous processors
published pages: 797-822, ISSN: 1066-8888, DOI: 10.1007/s00778-018-0512-y
The VLDB Journal 27/6 2020-03-04
2019 Georgios Mylonas Dimitrios Amaxilatis Stelios Tsampas Lidia Pocero Joakim Gunneriusson
A Methodology for Saving Energy in Educational Buildings Using an IoT Infrastructure
published pages: , ISSN: , DOI:
10th International Conference on Information, Intelligence, Systems and Applications (IISA 2019) 2020-03-04
2019 Steffen Zeuch, Bonaventura Del Monte, Jeyhun Karimov, Clemens Lutz, Manuel Renz, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl
Analyzing efficient stream processing on modern hardware
published pages: 516-530, ISSN: 2150-8097, DOI: 10.14778/3303753.3303758
Proceedings of the VLDB Endowment 12/5 2020-03-04

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The information about "E2DATA" are provided by the European Opendata Portal: CORDIS opendata.

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