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RECIPE SIGNED

REliable power and time-ConstraInts-aware Predictive management of heterogeneous Exascale systems

Total Cost €

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EC-Contrib. €

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Partnership

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 RECIPE project word cloud

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

sme    optimizing    hospital    15    performance    proactive    machine    energy    academic    evolution    hierarchical    magnitude    issue    methodology    decreasing    guarantees    enforcing    heterogeneity    failures    power    watt    computation    goals    reasonable    efficiency    hpc    heterogeneous    reliability    epfl    hardware    25    recipe    budgets    quantitative    mean    interact    exploration    upv    ranging    gap    domains    centers    world    analytics    relies    architecture    deep    psnc    improvement    integration    middleware    resource    predictive    chuv    models    oriented    throughput    learning    geophysical    critical    disaggregate    delay    facilities    cases    transient    few    grow    variety    infrastructure    executions    exascale    runtime    underlying    timing    thermal    handle    data    biomedical    qos    close    faulty    meteorology    time    provides    layers    ibts    deeply    bsc    complexity    manager    mttf    enormous    cerict    20    supercomputing    avenues    industry    polimi   

Project "RECIPE" data sheet

The following table provides information about the project.

Coordinator
POLITECNICO DI MILANO 

Organization address
address: PIAZZA LEONARDO DA VINCI 32
city: MILANO
postcode: 20133
website: www.polimi.it

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 Italy [IT]
 Total cost 3˙290˙800 €
 EC max contribution 3˙285˙300 € (100%)
 Programme 1. H2020-EU.1.2.2. (FET Proactive)
 Code Call H2020-FETHPC-2017
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-05-01   to  2021-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    POLITECNICO DI MILANO IT (MILANO) coordinator 705˙000.00
2    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE CH (LAUSANNE) participant 465˙250.00
3    UNIVERSITAT POLITECNICA DE VALENCIA ES (VALENCIA) participant 437˙000.00
4    BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION ES (BARCELONA) participant 410˙500.00
5    INSTYTUT CHEMII BIOORGANICZNEJ POLSKIEJ AKADEMII NAUK PL (POZNAN) participant 397˙250.00
6    Centro Regionale Information Communication Technology scrl IT (Benevento) participant 395˙500.00
7    INTELLIGENCE BEHIND THINGS SOLUTIONS SRL IT (MONZA) participant 290˙500.00
8    CENTRE HOSPITALIER UNIVERSITAIRE VAUDOIS CH (LAUSANNE) participant 184˙300.00

Map

 Project objective

The current HPC facilities will need to grow by an order of magnitude in the next few years to reach the Exascale range. The dedicated middleware needed to manage the enormous complexity of future HPC centers, where deep heterogeneity is needed to handle the wide variety of applications within reasonable power budgets, will be one of the most critical aspects in the evolution of HPC infrastructure towards Exascale. This middleware will need to address the critical issue of reliability in face of the increasing number of resources, and therefore decreasing mean time between failures. To close this gap, RECIPE provides: a hierarchical runtime resource management infrastructure optimizing energy efficiency and ensuring reliability for both time-critical and throughput-oriented computation; a predictive reliability methodology to support the enforcing of QoS guarantees in face of both transient and long-term hardware failures, including thermal, timing and reliability models; and a set of integration layers allowing the resource manager to interact with both the application and the underlying deeply heterogeneous architecture, addressing them in a disaggregate way. Quantitative goals for RECIPE include: 25% increase in energy efficiency (performance/watt) with an 15% MTTF improvement due to proactive thermal management; energy-delay product improved up to 25%; 20% reduction of faulty executions. The project will assess its results against the following set of real world use cases, addressing key application domains ranging from well established HPC applications such as geophysical exploration and meteorology, to emerging application domains such as biomedical machine learning and data analytics. To this end, RECIPE relies on a consortium composed of four leading academic partners (POLIMI,UPV,EPFL,CeRICT); two supercomputing centers, BSC and PSNC; a research hospital, CHUV, and an SME, IBTS, which provide effective exploitation avenues through industry-based use cases

 Publications

year authors and title journal last update
List of publications.
2019 Federico Reghenzani, Giuseppe Massari, William Fornaciari
The Misconception of Exponential Tail Upper-Bounding in Probabilistic Real-Time
published pages: 1-1, ISSN: 1943-0663, DOI: 10.1109/les.2018.2889114
IEEE Embedded Systems Letters 2020-01-27

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

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