Toward Comprehensive Specification of Distributed Systems

A new approach to modelling distributed systems is presented. It uses sequential processes and event synchronization as building blocks to construct a cohesive picture of the interdependent requirements for the functionality, architecture, scheduling policies, and performance attributes of a distributed system. A language called CSPS (an extension of Hoare\u27s CSP) is used in the illustration of the approach. Employing CSP as a base allows modelled systems to be verified using techniques already developed for verifying CSP programs and leads to the emergence of a uniform incremental strategy for verifying both logical and performance properties of distributed systems. Several small distributed systems have been modelled using this approach. These exercises enabled us to evaluate the notation system and to gain some expertise on how to approach the specification of distributed systems. This paper describes one of the models and the modelling strategy that has emerged from these exercises

On the engineering of crucial software

The various aspects of the conventional software development cycle are examined. This cycle was the basis of the augmented approach contained in the original grant proposal. This cycle was found inadequate for crucial software development, and the justification for this opinion is presented. Several possible enhancements to the conventional software cycle are discussed. Software fault tolerance, a possible enhancement of major importance, is discussed separately. Formal verification using mathematical proof is considered. Automatic programming is a radical alternative to the conventional cycle and is discussed. Recommendations for a comprehensive approach are presented, and various experiments which could be conducted in AIRLAB are described

Philosophy of Blockchain Technology - Ontologies

About the necessity and usefulness of developing a philosophy specific to the blockchain technology, emphasizing on the ontological aspects. After an Introduction that highlights the main philosophical directions for this emerging technology, in Blockchain Technology I explain the way the blockchain works, discussing ontological development directions of this technology in Designing and Modeling. The next section is dedicated to the main application of blockchain technology, Bitcoin, with the social implications of this cryptocurrency. There follows a section of Philosophy in which I identify the blockchain technology with the concept of heterotopia developed by Michel Foucault and I interpret it in the light of the notational technology developed by Nelson Goodman as a notational system. In the Ontology section, I present two developmental paths that I consider important: Narrative Ontology, based on the idea of order and structure of history transmitted through Paul Ricoeur's narrative history, and the Enterprise Ontology system based on concepts and models of an enterprise, specific to the semantic web, and which I consider to be the most well developed and which will probably become the formal ontological system, at least in terms of the economic and legal aspects of blockchain technology. In Conclusions I am talking about the future directions of developing the blockchain technology philosophy in general as an explanatory and robust theory from a phenomenologically consistent point of view, which allows testability and ontologies in particular, arguing for the need of a global adoption of an ontological system for develop cross-cutting solutions and to make this technology profitable. CONTENTS: Abstract Introducere Tehnologia blockchain - Proiectare - Modele Bitcoin Filosofia Ontologii - Ontologii narative - Ontologii de intreprindere Concluzii Note Bibliografie DOI: 10.13140/RG.2.2.24510.3360

SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization

Computer vision is experiencing an AI renaissance, in which machine learning models are expediting important breakthroughs in academic research and commercial applications. Effectively training these models, however, is not trivial due in part to hyperparameters: user-configured values that control a model's ability to learn from data. Existing hyperparameter optimization methods are highly parallel but make no effort to balance the search across heterogeneous hardware or to prioritize searching high-impact spaces. In this paper, we introduce a framework for massively Scalable Hardware-Aware Distributed Hyperparameter Optimization (SHADHO). Our framework calculates the relative complexity of each search space and monitors performance on the learning task over all trials. These metrics are then used as heuristics to assign hyperparameters to distributed workers based on their hardware. We first demonstrate that our framework achieves double the throughput of a standard distributed hyperparameter optimization framework by optimizing SVM for MNIST using 150 distributed workers. We then conduct model search with SHADHO over the course of one week using 74 GPUs across two compute clusters to optimize U-Net for a cell segmentation task, discovering 515 models that achieve a lower validation loss than standard U-Net.Comment: 10 pages, 6 figure

Special Session on Industry 4.0

No abstract available