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DataLocAbstractions SIGNED

Advanced Programming Environments for Exascale Data-Centric Computing

Total Cost €

EC-Contrib. €

Partnership

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Outcomes and
results

DataLocAbstractions project word cloud

Explore the words cloud of the DataLocAbstractions project. It provides you a very rough idea of what is the project "DataLocAbstractions" about.

motivating shifted compute computing primary integrate paradigm source locality centric class chips emerged parallel energy performance abstractions provides reinventing efficiency architectural thousand power takes equipped api expose programming smooth concurrency consumption requiring data environment realities decade exascale leadership technologies dual ultimate platforms parallelism interface constraint chip reflect theoretical combustion foundation turbulent 2048 critical embodied hpc proposes movement shift dominant environments core generation transition criterion life

Project "DataLocAbstractions" data sheet

The following table provides information about the project.

Coordinator	KOC UNIVERSITY Organization address address: RUMELI FENERI YOLU SARIYER city: ISTANBUL postcode: 34450 website: www.ku.edu.tr 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	Turkey [TR]
Project website	http://parcorelab.ku.edu.tr
Total cost	145˙845 €
EC max contribution	145˙845 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2014
Funding Scheme	MSCA-IF-EF-RI
Starting year	2015
Duration (year-month-day)	from 2015-04-01 to 2017-03-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	KOC UNIVERSITY KOC UNIVERSITY Organization address address: RUMELI FENERI YOLU SARIYER city: ISTANBUL postcode: 34450 website: www.ku.edu.tr contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	TR (ISTANBUL)	coordinator	145˙845.00

Map

Project objective

Power efficiency has emerged as the primary design constraint for the next generation of computing systems and the dominant source of energy consumption has shifted from computing elements to the movement of data. This shift will make locality of data the new programming challenge of the decade. However, current programming environments take a compute-centric approach and do not reflect the realities of the architectural trends. For performance and energy efficiency reasons, there is a critical need for a new data-centric programming paradigm that takes data locality as a primary criterion. Moreover the next generation of high performance systems (Exascale Systems) will be equipped with 2048-core chips, requiring applications to expose over a thousand-way concurrency. For a smooth transition to these advanced technologies, this project proposes a theoretical foundation and programming abstractions; embodied in an API (Application Programming Interface) that provides a rich interface to address the dual challenges of data locality and increased on-chip parallelism for emerging parallel computing systems. The ultimate goal of the project is to integrate the proposed API into real-life applications that are of great interest to Europe. The project will study Turbulent Combustion as a motivating application class because of its importance in energy production. The proposed research, by reinventing the programming environment to better reflect the realities of future platforms, will facilitate the transition to Exascale of applications that are critical for strengthening European leadership in HPC.

Publications

List of publications.
year	authors and title	journal	last update
2017	Didem Unat, Anshu Dubey, Torsten Hoefler, John Shalf, Mark Abraham, Mauro Bianco, Bradford L. Chamberlain, Romain Cledat, H. Carter Edwards, Hal Finkel, Karl Fuerlinger, Frank Hannig, Emmanuel Jeannot, Amir Kamil, Jeff Keasler, Paul H J Kelly, Vitus Leung, Hatem Ltaief, Naoya Maruyama, Chris J. Newburn, Miquel Pericas Trends in Data Locality Abstractions for HPC Systems published pages: 1-1, ISSN: 1045-9219, DOI: 10.1109/TPDS.2017.2703149	IEEE Transactions on Parallel and Distributed Systems 10 May 2017	2019-06-13
2016	Weiqun Zhang, Ann Almgren, Marcus Day, Tan Nguyen, John Shalf, Didem Unat BoxLib with Tiling: An Adaptive Mesh Refinement Software Framework published pages: S156-S172, ISSN: 1064-8275, DOI: 10.1137/15M102616X	SIAM Journal on Scientific Computing 38/5	2019-06-13

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