BSC Training Course: Simplifying the usage of persistent distributed data with Hecuba @BSC
Objectives
The objective of this course is to give an overview of BSC storage solutions with Hecuba. This platform allows to easily store and manipulate distributed data from object-oriented applications, enabling programmers to handle object persistence using the same classes they use in their programs, thus avoiding time consuming transformations between persistent and non-persistent data models. Also, Hecuba enables programmers to transparently manage distributed data, without worrying about its location. This is achieved by adding a minimal set of annotations in the classes.
Hecuba can work independently or integrated with the COMPSs programming model and runtime to facilitate parallelization of applications that handle persistent data, thus providing a comprehensive mechanism that enables the efficient usage of persistent storage solutions from distributed programming environments.
Hecuba platform offer a common interface to the application developer that facilitates using one solution or the other depending on the needs, without changing the application code. It also has additional features that allow the programmer to take advantage of their particularities.
Requirements
Basic programming skills in Python and Java.
Previous attendance to PATC course on programming distributed systems with COMPSs is recommended.
Learning Outcomes
In the course, the Hecuba syntax, programming methodology and an overview of their internals will be given. Also, an overview of COMPSs at user level will be provided in order to take advantage of the distribution of data with both platforms. The attendees will get a first lesson about programming with the common storage interface that will enable them to start programming with the framework.
A hands-on with simple introductory exercises will be also performed, with and without COMPSs to distribute the computation. The students who finish this course will be able to develop simple Hecuba applications and to run them both in a local resource and in a distributed platform (initially in a private cloud)
Academic Staff
Course Conveners
Department and Research group: Computer Science - Workflows and Distributed Computing
Course Lecturers
Department and Research group: Computer Sciences - Workflows and Distributed Computing
Yolanda Becerra, Data-driven Scientific Computing research line, Senior researcher
Juanjo Costa, Computer Architecture Department at UPC
Materials
INTELLECTUAL PROPERTY RIGHTS NOTICE:
• The User may only download, make and retain a copy of the materials for his/her use for non‐commercial and research purposes.
• The User may not commercially use the material, unless has been granted prior written consent by the Licensor to do so; and cannot remove, obscure or modify copyright notices, text acknowledging or other means of identification or disclaimers as they appear.
• For further details, please contact BSC‐CNS patc@bsc.es
Further information
BSC Training Courses do not charge fees.
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Sponsor: BSC