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Overview and summary of optimisation requirements

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Research Infrastructures

The following RIs contributed to developing optimisation requirements

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SIOS:Many optimisation problems, whether explicitly identified as such by RIs for implicit in the requirements of other topics, can be reduced down to ones of data placement. Is the data need by researchers available in a location from which it can be easily identified, retrieved and analysed, in whole or in part? Is it feasible to perform analysis on that data without substantial additional preparation, and if not, what is the overhead in time and effort required to prepare the data for processing? This latter question relates to the notion of data staging, whereby data is placed and prepared for processing on some computational service (whether provided on a researcher's desktop, an HPC cluster or a web server), which in turn concerns the further question of whether data should be brought to where they can be best computed, or computing tasks brought to where the data currently reside. Given the large size of many RI's primary datasets, bringing computation to data is appealing, but the complexity of various analyses also often requires supercomputing-level resources, which require the data be staged at a computing facility such as are brokered in Europe by PRACE.

Reductionism aside however, the key performance indicator used by most RIs is researcher productivity. Can researchers use the RI to efficiently locate the data they need? Do they have access to all the support available for processing the data and conducting their experiments? Can they replicate the cited results of their peers using the facilities provided? This raises yet another question: how does the service provided to researchers translate to requirements on data placement and infrastructure availability?

Research Infrastructures

The following RIs contributed to developing optimisation requirements:

IS-ENES2: This RI has an interest in: standardised interfaces for interacting with services; automated replication procedures for ensuring the availability of data across all continents; policies for the assignment of compute resources to user groups; funding for community computing resources.