Machine Learning (ML) and Deep Learning (DL) are two technologies used to extract representations of the data for a specific purpose. ML algorithms take a set of data as input to generate one or several predictions. To define the final version of one model, usually there is an initial step devoted to train the algorithm [...]
This technical report will try to give an overview of different profiling tools, both open-source and commercial. Some of them are currently available in FinisTerraeII supercomputer, so a brief usage of this tools will be shown too. This report will give a point of reference to start to use this tools, and at the same [...]
The purpose of this Technical Report is analyze, debug & benchmark the BigData platform installed at CESGA by running Spark-based ML algorithms over public datasets with different resource allocation (number of executors, number of cores, memory per executor, memory for driver, etc.).
This internal technical document reports the hyper-parametric search for the proposed Neural Network model using Tensorflow and Finis Terrae II. The NN model helps to manage the process of Laser Metal Deposition based on the thermal images from a thermal camera attached to the laser header that record a complete process. This case is an [...]
This technical report shows the behaviour of Lustre storage subsystem for different applications. Lustre is a scalable file subsystem and let the final user to control the way her files are stored. CESGA has 694,5TB usable in Finis Terrae II supercomputer, and the Infiniband network achieves better results than DAS storage. This report is intended [...]
Este informe recoge los principales resultados extraídos del estudio del rendimiento de diferentes herramientas de paralelización en el superordenador Finis Terrae II instalado en el CESGA. Se incluyen resultados tanto de los rendimientos de comunicaciones punto a punto como de comunicaciones colectivas, en las que se analiza como afecta el aumento del número de procesos [...]
En el CESGA gran parte de servicios hacen uso de BBDD de tipo MySQL. Se pretende la mejora de la disponibilidad de dichos servicios analizando soluciones de clúster.