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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.

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

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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