Abstract:
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In the recent joint venture between High-Performance Computing (HPC) and Big-Data
(BD) Ecosystems towards the Exascale Computing, the scientific community has realized
that powerful programming models and high-level abstraction tools are a must. Within this
context, the Barcelona Supercomputing Center (BSC) is developing the COMP Superscalar
(COMPSs) programming model, whose main objective is to develop applications in a sequential
way, while the Runtime System handles the inherent parallelism of the application
and abstracts the programmer from the different underlying infrastructures. The parallelism
is achieved by defining an application Interface that allows COMPSs to detect methods that
operate on a set of parameters (called tasks), and execute them distributedly and transparently.
This Master Thesis aims to enhance COMPSs, adapting it to the needs of the Big-Data
Ecosystems, by supporting Analytic and HPC workflows. To this end, we propose a straightforward
integration with the execution of binaries, and MPI and OmpSs applications. Although
the COMPSs programming model is kept untouched, we extend the COMPSs Annotations
and some of the COMPSs internals such as the task schedulers and the worker
executors.
To support our contribution, we have ported to COMPSs two real use cases. On the
one hand, NMMB BSC-Dust, a workflow to predict the atmospheric life cycle of the desert
dust and, on the other hand, Guidance, an integrated solution for Genome and Phenome
association analysis. |