Domain-aware Genetic Algorithms for Hardware and Mapping Optimization for Efficient DNN Acceleration

The proliferation of AI across a variety of domains (vision, language, speech, recommendations, games) has led to the rise of domain-specific accelerators for deep learning. At design-time, these accelerators carefully architect the on-chip dataflow to maximize data reuse (over space and time) and size the hardware resources (PEs and buffers) to maximize performance and energy-efficiency, while meeting the chip’s area and power targets. At compile-time, the target Deep Neural Network (DNN) model is mapped over the accelerator. The mapping refers to tiling the computation and data (i.e., tensors) and scheduling them over the PEs and scratchpad buffers respectively, while honoring the microarchitectural constraints (number of PEs, buffer sizes, and dataflow). The design-space of valid hardware resource assignments for a given dataflow and the valid mappings for a given hardware is extremely large (~O(10^24)) per layer for state-of-the-art DNN models today. This makes exhaustive searches infeasible. Unfortunately, there can be orders of magnitude performance and energy-efficiency differences between an optimal and sub-optimal choice, making these decisions a crucial part of the entire design process. Moreover, manual tuning by domain experts become unprecedentedly challenged due to increased irregularity (due to neural architecture search) and sparsity of DNN models. This necessitate the existence of Map Space Exploration (MSE). In this thesis, our goal is to deliver a deep analysis of the MSE for DNN accelerators, propose different techniques to improve MSE, and generalize the MSE framework to a wider landscape (from mapping to HW-mapping co-exploration, from single-accelerator to multi-accelerator scheduling). As part of it, we discuss the correlation between hardware flexibility and the formed map space, formalized the map space representation by four mapping axes: tile, order, parallelism, and shape. Next, we develop dedicated exploration operators for these axes and use genetic algorithm framework to converge the solution. Next, we develop "sparsity-aware" technique to enable sparsity consideration in MSE and a "warm-start" technique to solve the search speed challenge commonly seen across learning-based search algorithms. Finally, we extend out MSE to support hardware and map space co-exploration and multi-accelerator scheduling.Ph.D

Model for WCET prediction, scheduling and task allocation for emergent agent-behaviours in real-time scenarios

[ES]Hasta el momento no se conocen modelos de tiempo real específicamente desarrollados para su uso en sistemas abiertos, como las Organizaciones Virtuales de Agentes (OVs). Convencionalmente, los modelos de tiempo real se aplican a sistemas cerrados donde todas las variables se conocen a priori. Esta tesis presenta nuevas contribuciones y la novedosa integración de agentes en tiempo real dentro de OVs. Hasta donde alcanza nuestro conocimiento, éste es el primer modelo específicamente diseñado para su aplicación en OVs con restricciones temporales estrictas. Esta tesis proporciona una nueva perspectiva que combina la apertura y dinamicidad necesarias en una OV con las restricciones de tiempo real. Ésto es una aspecto complicado ya que el primer paradigma no es estricto, como el propio término de sistema abierto indica, sin embargo, el segundo paradigma debe cumplir estrictas restricciones. En resumen, el modelo que se presenta permite definir las acciones que una OV debe llevar a cabo con un plazo concreto, considerando los cambios que pueden ocurrir durante la ejecución de un plan particular. Es una planificación de tiempo real en una OV. Otra de las principales contribuciones de esta tesis es un modelo para el cálculo del tiempo de ejecución en el peor caso (WCET). La propuesta es un modelo efectivo para calcular el peor escenario cuando un agente desea formar parte de una OV y para ello, debe incluir sus tareas o comportamientos dentro del sistema de tiempo real, es decir, se calcula el WCET de comportamientos emergentes en tiempo de ejecución. También se incluye una planificación local para cada nodo de ejecución basada en el algoritmo FPS y una distribución de tareas entre los nodos disponibles en el sistema. Para ambos modelos se usan modelos matemáticos y estadísticos avanzados para crear un mecanismo adaptable, robusto y eficiente para agentes inteligentes en OVs. El desconocimiento, pese al estudio realizado, de una plataforma para sistemas abiertos que soporte agentes con restricciones de tiempo real y los mecanismos necesarios para el control y la gestión de OVs, es la principal motivación para el desarrollo de la plataforma de agentes PANGEA+RT. PANGEA+RT es una innovadora plataforma multi-agente que proporciona soporte para la ejecución de agentes en ambientes de tiempo real. Finalmente, se presenta un caso de estudio donde robots heterogéneos colaboran para realizar tareas de vigilancia. El caso de estudio se ha desarrollado con la plataforma PANGEA+RT donde el modelo propuesto está integrado. Por tanto al final de la tesis, con este caso de estudio se obtienen los resultados y conclusiones que validan el modelo

Unmanned Aircraft Systems in the Cyber Domain

Unmanned Aircraft Systems are an integral part of the US national critical infrastructure. The authors have endeavored to bring a breadth and quality of information to the reader that is unparalleled in the unclassified sphere. This textbook will fully immerse and engage the reader / student in the cyber-security considerations of this rapidly emerging technology that we know as unmanned aircraft systems (UAS). The first edition topics covered National Airspace (NAS) policy issues, information security (INFOSEC), UAS vulnerabilities in key systems (Sense and Avoid / SCADA), navigation and collision avoidance systems, stealth design, intelligence, surveillance and reconnaissance (ISR) platforms; weapons systems security; electronic warfare considerations; data-links, jamming, operational vulnerabilities and still-emerging political scenarios that affect US military / commercial decisions. This second edition discusses state-of-the-art technology issues facing US UAS designers. It focuses on counter unmanned aircraft systems (C-UAS) – especially research designed to mitigate and terminate threats by SWARMS. Topics include high-altitude platforms (HAPS) for wireless communications; C-UAS and large scale threats; acoustic countermeasures against SWARMS and building an Identify Friend or Foe (IFF) acoustic library; updates to the legal / regulatory landscape; UAS proliferation along the Chinese New Silk Road Sea / Land routes; and ethics in this new age of autonomous systems and artificial intelligence (AI).https://newprairiepress.org/ebooks/1027/thumbnail.jp

Proceedings of the Conference on Production Systems and Logistics: CPSL 2022

[no abstract available

Optimisation du placement et de l’assignation de fréquences d’antennes dans un réseau de télécommunications

« RÉSUMÉ : Les nombreux services de communication mobile disponibles aujourd'hui reposent sur des réseaux d'infrastructures exploités par des opérateurs de télécommunications. Pour rester compétitifs, ils doivent s'adapter à la demande du marché et faire face à la croissance permanente du nombre d'utilisateurs ainsi qu'à l'augmentation de leurs exigences en termes de services et de couverture géographique. Il leur faut pour cela constamment améliorer leurs réseaux en mettant à niveau leurs installations existantes et en en ajoutant de nouvelles. Le déploiement et l'entretien d'un réseau de télécommunications étant très onéreux, la minimisation du coût lié aux infrastructures est un enjeu très important pour les opérateurs. Or les réseaux de télécommunications sont aujourd'hui devenus des systèmes très complexes, composés d'éléments variés et dépendant de très nombreux paramètres qui doivent être pris en compte lors de leur conception. La difficulté de conception d'un réseau est donc très élevée et il serait intéressant pour les opérateurs de pouvoir se munir d'outils d'optimisation conçus pour les aider dans cette tâche. Le présent travail se propose de poser les bases d'une nouvelle méthode d'optimisation d'un réseau de télécommunications, dans le but de permettre le développement futur de tels outils d'aide à la décision pour la conception de réseaux de télécommunications. Les constituants de base d'un réseau de télécommunications sont les antennes ou stations de base, qui doivent être placées judicieusement sur le territoire à couvrir pour fournir un service à tous les usagers. La difficulté de placement des antennes provient du fait que des antennes émettant aux mêmes fréquences interfèrent entre elles, donnant aux zones de couverture de chacune des formes irrégulières et sensibles aux variations de position et de fréquence. La méthode développée ici s'attache à optimiser la localisation des antennes conjointement avec leur assignation de fréquence. La démarche utilisée se décompose en deux étapes principales. Il est d'abord nécessaire de développer un modèle de réseau de télécommunications adapté à l'optimisation que l'on souhaite en faire et de l'implémenter sous forme de programme informatique afin d'effectuer des simulations. Le modèle doit être suffisamment précis pour donner des résultats concordant avec la réalité mais sans être trop complexe pour que les simulations puissent s'exécuter en un temps court. Un algorithme d'optimisation est ensuite développé, utilisant une méthode de recherche directe, l'algorithme MADS, et une métaheuristique, la recherche tabou, et traitant la simulation de réseau comme une boîte noire à optimiser. La méthode est testée avec différentes instances et les résultats sont présentés et analysés. Les résultats obtenus sont encourageants, en particulier avec l'instance correspondant à un territoire réel. La méthode semble donc pouvoir être utilisée comme point de départ pour le développement d'outils d'optimisation de réseaux de télécommunications.»----------« ABSTRACT : All the mobile communication services available today rely on networks operated by telecommunications companies. To remain competitive, they have to conform to the market and cope with the ever growing number of users and the increase in their demands in terms of services and geographic coverage. They need to constantly improve their networks by upgrading their facilities and adding new ones. Expanding and maintaining a telecommunications network is very expensive, therefore minimizing the costs related to networks is a very important issue for operators. And yet, telecommunications networks have now become very complex systems, made up of various elements and depending on a large number of parameters which have to be considered when designing a network. Thus it is a difficult task and it would be very interesting for operators to have optimization tools to help them. The present work intends to lay the foundations for a new telecommunications network optimization method, in order to enable the future development of tools to help in the process of designing a network. The components at the root of a telecommunications network are antennas or base stations, which have to be placed wisely on the target territory in order to supply all users with mobile service. Placing antennas is difficult because antennas emitting at the same frequencies interfere, and the shape of their coverage zones can then be irregular and sensitive to variations of localization and frequencies. The goal of the method developed here is to optimize the localization of the antennas together with their frequency allocation. The approach used in this work breaks down into two stages. First, a telecommunications network model suitable to the optimization is developed and implemented as a computer program in order to perform simulations. The model needs to be accurate enough to give realistic results, but not to complex so as to allow quick simulations. An optimization algorithm is then developed, which uses a direct search method, the MADS algorithm, and a metaheuristic, the tabu search, and handles the network simulation as a black-box. The method is tested on various instances and results are presented and analysed. The results are encouraging, especially with the instance corresponding to an actual territory. Therefore the method seems a promising first step in the development of telecommunications networks optimization tools.

An evaluation of the challenges of Multilingualism in Data Warehouse development

In this paper we discuss Business Intelligence and define what is meant by support for Multilingualism in a Business Intelligence reporting context. We identify support for Multilingualism as a challenging issue which has implications for data warehouse design and reporting performance. Data warehouses are a core component of most Business Intelligence systems and the star schema is the approach most widely used to develop data warehouses and dimensional Data Marts. We discuss the way in which Multilingualism can be supported in the Star Schema and identify that current approaches have serious limitations which include data redundancy and data manipulation, performance and maintenance issues. We propose a new approach to enable the optimal application of multilingualism in Business Intelligence. The proposed approach was found to produce satisfactory results when used in a proof-of-concept environment. Future work will include testing the approach in an enterprise environmen

LIPIcs, Volume 258, SoCG 2023, Complete Volume

LIPIcs, Volume 258, SoCG 2023, Complete Volum