Innovating Works

ExCAPE

Financiado
Exascale Compound Activity Prediction Engine
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... 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. ver más
31/08/2018
IMEC
4M€
Duración del proyecto: 38 meses Fecha Inicio: 2015-06-24
Fecha Fin: 2018-08-31

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2018-08-31
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
FETHPC-1-2014: HPC Core Technologies, Programming Environments and Algorithms for Extreme Parallelism and Extreme Data Applications
Cerrada hace 9 años
Presupuesto El presupuesto total del proyecto asciende a 4M€
Líder del proyecto
INTERUNIVERSITAIR MICROELECTRONICA CENTRUM No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5