Opendata, web and dolomites

CoupledDB

High-Performance Indexing for Emerging GPU-Coupled Databases

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 CoupledDB project word cloud

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

responsive    principal    confluence    setting    exclusively    cut    algorithms    becomes    objects    vastly    gpu    types    mobile    trajectories    leverage    techniques    accelerators    energy    foundational    competitiveness    frequently    heterogeneity    positioning    accessed    structures    incorporating    researcher    forwardly    database    powerful    data    computation    action    neurons    lower    greener    heterogeneous    idle    model    indexes    faster    index    preliminary    disruptive    stage    commonplace    deescalating    vehicle    indexing    valuable    expertise    units    hot    performance    straight    graphics    gpus    disk    squander    skills    parallel    forefront    small    handling    productivity    connected    architecture    memory    host    scientific    building    industry    innovation    compute    parallelism    programming    ecosystem    simulations    proliferation    footprint    coupled    transfer    hardware    dichotomy    fact    exploits    sweeping    multicore    cross    processed    suggest    ubiquitous    computational    soon    feasible    cheaper   

Project "CoupledDB" data sheet

The following table provides information about the project.

Coordinator
NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU 

Organization address
address: HOGSKOLERINGEN 1
city: TRONDHEIM
postcode: 7491
website: www.ntnu.no

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 Norway [NO]
 Project website https://www.ntnu.edu/idi/groups/dart
 Total cost 208˙400 €
 EC max contribution 208˙400 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-05-01   to  2019-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU NO (TRONDHEIM) coordinator 208˙400.00

Map

 Project objective

'Index structures are foundational to the performance of database systems and large-scale simulations. Even small advances in indexing can therefore have widespread, sweeping impact on both industry competitiveness and scientific productivity. The confluence of several hardware trends is setting the stage for disruptive innovation in database indexing: deescalating costs of memory make it feasible to organise most of the 'hot', frequently accessed data in memory rather than on disk; and increasingly commonplace accelerators such as graphics processing units (GPUs) offer large-scale parallelism with a lower energy footprint. Thus, in-memory indexing that exploits GPUs could be much cheaper, faster, and greener.

However, effectively incorporating GPUs into computation is a principal research challenge. To idle the powerful multicore system in favour of exclusively using the GPU connected to it, as done currently, is to squander valuable resources. On the other hand, the GPU has a vastly different computational model, so cannot straight-forwardly leverage multicore techniques. The challenges in handling this dichotomy, in fact, will cross-cut many research areas as the heterogeneity in the compute ecosystem becomes ubiquitous in parallel processing.

Building on preliminary results that suggest common data structures processed by architecture-specific algorithms can support heterogeneity, this action will design indexes for the coupled multicore-GPU database systems that will soon be ubiquitous. The indexes will enable more responsive simulations of complex objects such as neurons and vehicle trajectories and support the recent proliferation of mobile-generated data. Moreover, through the action, the researcher will transfer technical parallel programming skills to the host, while the host will transfer expertise about new data types to the researcher. The project results will contribute to Europe's positioning at the forefront of heterogeneous parallel processing.'

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "COUPLEDDB" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.2.)

TOPOCIRCUS (2019)

Simulations of Topological Phases in Superconducting Circuits

Read More  

ICARUS (2020)

Information Content of locAlisation: fRom classical to qUantum Systems

Read More  

EVOMET (2019)

The rise and fall of metastatic clones under immune attack

Read More