Unveiling User Behavior on Summit Login Nodes as a User

We observe and analyze usage of the login nodes of the leadership class Summit supercomputer from the perspective of an ordinary user -- not a system administrator -- by periodically sampling user activities (job queues, running processes, etc.) for two full years (2020-2021). Our findings unveil key usage patterns that evidence misuse of the system, including gaming the policies, impairing I/O performance, and using login nodes as a sole computing resource. Our analysis highlights observed patterns for the execution of complex computations (workflows), which are key for processing large-scale applications.Comment: International Conference on Computational Science (ICCS), 202

A cloudification methodology for high performance simulations

Mención Internacional en el título de doctorMany scientific areas make extensive use of computer simulations to study complex real-world processes. These computations are typically very resource-intensive and present scalability issues as experiments get larger, even in dedicated supercomputers since they are limited by their own hardware resources. Cloud computing raises as an option to move forward into the ideal unlimited scalability by providing virtually infinite resources, yet applications must be adapted to this paradigm. The major goal of this thesis is to analyze the suitability of performing simulations in clouds by performing a paradigm shift, from classic parallel approaches to data-centric models, in those applications where that is possible. The aim is to maintain the scalability achieved in traditional HPC infrastructures, while taking advantage of Cloud Computing paradigm features. The thesis also explores the characteristics that make simulators suitable or unsuitable to be deployed on HPC or Cloud infrastructures, defining a generic architecture and extracting common elements present among the majority of simulators. As result, we propose a generalist cloudification methodology based on the MapReduce paradigm to migrate high performance simulations into the cloud to provide greater scalability. We analysed its viability by applying it to a real engineering simulator and running the resulting implementation on HPC and cloud environments. Our evaluations will aim to show that the cloudified application is highly scalable and there is still a large margin to improve the theoretical model and its implementations, and also to extend it to a wider range of simulations.Muchas áreas de investigación hacen uso extensivo de simulaciones informáticas para estudiar procesos complejos del mundo real. Estas simulaciones suelen hacer uso intensivo de recursos, y presentan problemas de escalabilidad conforme los experimentos aumentan en tamaño incluso en clústeres, ya que estos están limitados por sus propios recursos hardware. Cloud Computing (computación en la nube) surge como alternativa para avanzar hacia el ideal de escalabilidad ilimitada mediante el aprovisionamiento de infinitos recursos (de forma virtual). No obstante, las aplicaciones deben ser adaptadas a este nuevo paradigma. La principal meta de esta tesis es analizar la idoneidad de realizar simulaciones en la nube mediante un cambio de paradigma, de las clásicas aproximaciones paralelas a nuevos modelos centrados en los datos, en aquellas aplicaciones donde esto sea posible. El objetivo es mantener la escalabilidad alcanzada en las tradicionales infraestructuras HPC, mientras se explotan las ventajas del paradigma de computación en la nube. La tesis explora las características que hacen a los simuladores ser o no adecuados para ser desplegados en infraestructuras clúster o en la nube, definiendo una arquitectura genérica y extrayendo elementos comunes presentes en la mayoría de los simuladores. Como resultado, proponemos una metodología genérica de cloudificación, basada en el paradigma MapReduce, para migrar simulaciones de alto rendimiento a la nube con el fin de proveer mayor escalabilidad. Analizamos su viabilidad aplicándola a un simulador real de ingeniería, y ejecutando la implementación resultante en entornos clúster y en la nube. Nuestras evaluaciones pretenden mostrar que la aplicación cloudificada es altamente escalable, y que existe un amplio margen para mejorar el modelo teórico y sus implementaciones, y para extenderlo a un rango más amplio de simulaciones.- Administrador de Infraestructuras Ferroviarias (ADIF), Estudio y realización de programas de cálculo de pórticos rígidos de catenaria (CALPOR) y de sistema de simulación de montaje de agujas aéreas de línea aérea de contacto (SIA), JM/RS 3.6/4100.0685-9/00100 – Administrador de Infraestructuras Ferroviarias (ADIF), Proyecto para la Investigación sobre la aplicación de las TIC a la innovación de las diferentes infraestructuras correspondientes a las instalaciones de electrificación y suministro de energía (SIRTE), JM/RS 3.9/1500.0009/0-00000 – Spanish Ministry of Education, TIN2010-16497, Scalable Input/Output techniques for high-performance distributed and parallel computing environments – Spanish Ministry of Economics and Competitiveness, TIN2013-41350-P, Técnicas de gestión escalable de datos para high-end computing systems – European Union, COST Action IC1305, ”Network for Sustainable Ultrascale Computing Platforms” (NESUS) – European Union, COST Action IC0805, ”Open European Network for High Performance Computing on Complex Environments” – Spanish Ministry of Economics and Competitiveness, TIN2011-15734-E, Red de Computación de Altas Prestaciones sobre Arquitecturas Paralelas Heterogéneas (CAPAP-H)Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: Domenica Talia.- Presidente: José Daniel García Sánchez.- Secretario: José Manuel Moya Fernánde

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma