January 24th, 2020
Heterogeneous architectures with nodes featuring accelerator cards or sockets are taking an important share in the HPC market, given their superiority in term of flop/watt with respect to CISC and RISC architecture.
To be effective on heterogeneous architecture applications usually requires important refactoring and adaptation, and many programming paradigms are available, some vendor specific and some other defined by an open standard,
but without a clear winner yet (e.g. as it is the case for message passing communications where there is MPI, available for all network technologies).
This school focus on software development techniques to address the implementation of new HPC applications and the re-factory of existing ones, in the era of heterogeneous, energy efficient, massively parallel architectures,
toward exascale, with theoretical lectures and hands-on sessions on the different most promising programming techniques and paradigms for accelerated computing.
Software engineering techniques and high productivity languages will complement lectures on parallel programming and porting toward new architectures, to allow the implementation of application that can be maintained across a complex and fast evolving HPC architectures.
The school is aimed at PRACE users, final year master students, PhD students, and young researchers in computational sciences and engineering, with different backgrounds, interested in applying the emerging technologies on high performance computing to their research.
Good knowledge of parallel programming with MPI and/or OpenMP, knowledge of FORTRAN and C languages. Basic knowledge of parallel computer architectures.
Attendance is free.
A grant of 300 EUR (for students working abroad) and 150 EUR (for students working in Italy) will be available for participants not funded by their institution and not working or living in the Bologna area. Documentation will be required. Lunches for the 5 days will be provided by Cineca. Each student will be given a two month access to the Cineca's supercomputing resources.
The support of CINI for the software engineering module is gratefully acknowledged.
