CORDIS
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Exascale Compound Activity Prediction Engine

Project information

Grant agreement ID: 671555

  • Start date

    1 September 2015

  • End date

    31 August 2018

Funded under:

H2020-EU.1.2.2.

  • Overall budget:

    € 3 910 140

  • EU contribution

    € 3 910 140

Coordinated by:

INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM

Belgium

Objective

Scalable machine learning of complex models on extreme data will be an important industrial application of exascale computers. In this project, we take the example of predicting compound bioactivity for the pharmaceutical industry, an important sector for Europe for employment, income, and solving the problems of an ageing society. Small scale approaches to machine learning have already been trialed and show great promise to reduce empirical testing costs by acting as a virtual screen to filter out tests unlikely to work. However, it is not yet possible to use all available data to make the best possible models, as algorithms (and their implementations) capable of learning the best models do not scale to such sizes and heterogeneity of input data. There are also further challenges including imbalanced data, confidence estimation, data standards model quality and feature diversity.

The ExCAPE project aims to solve these problems by producing state of the art scalable algorithms and implementations thereof suitable for running on future Exascale machines. These approaches will scale programs for complex pharmaceutical workloads to input data sets at industry scale. The programs will be targeted at exascale platforms by using a mix of HPC programming techniques, advanced platform simulation for tuning and and suitable accelerators.

Coordinator

INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM

Address

Kapeldreef 75
3001 Leuven

Belgium

Activity type

Research Organisations

EU Contribution

€ 873 146,25

Participants (8)

JANSSEN CILAG SA

Spain

EU Contribution

€ 448 707,50

VYSOKA SKOLA BANSKA - TECHNICKA UNIVERZITA OSTRAVA

Czechia

EU Contribution

€ 532 500

ASTRAZENECA AB

Sweden

EU Contribution

€ 403 125

UNIVERSITAT LINZ

Austria

EU Contribution

€ 371 623,75

AALTO KORKEAKOULUSAATIO SR

Finland

EU Contribution

€ 283 593,75

INTEL CORPORATION

Belgium

EU Contribution

€ 507 500

IDEACONSULT LIMITED LIABILITY COMPANY

Bulgaria

EU Contribution

€ 120 000

ROYAL HOLLOWAY AND BEDFORD NEW COLLEGE

United Kingdom

EU Contribution

€ 369 943,75

Project information

Grant agreement ID: 671555

  • Start date

    1 September 2015

  • End date

    31 August 2018

Funded under:

H2020-EU.1.2.2.

  • Overall budget:

    € 3 910 140

  • EU contribution

    € 3 910 140

Coordinated by:

INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM

Belgium