The future of computing beyond Moore's Law.

Moore's Law is a techno-economic model that has enabled the information technology industry to double the performance and functionality of digital electronics roughly every 2 years within a fixed cost, power and area. Advances in silicon lithography have enabled this exponential miniaturization of electronics, but, as transistors reach atomic scale and fabrication costs continue to rise, the classical technological driver that has underpinned Moore's Law for 50 years is failing and is anticipated to flatten by 2025. This article provides an updated view of what a post-exascale system will look like and the challenges ahead, based on our most recent understanding of technology roadmaps. It also discusses the tapering of historical improvements, and how it affects options available to continue scaling of successors to the first exascale machine. Lastly, this article covers the many different opportunities and strategies available to continue computing performance improvements in the absence of historical technology drivers. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'

Distributed Simulation of Heterogeneous and Real-time Systems

This work describes a framework for distributed simulation of cyber-physical systems (CPS). Modern CPS comprise large numbers of heterogeneous components, typically designed in very different tools and languages that are not or not easily composeable. Evaluating such large systems requires tools that integrate all components in a systematic, well-defined manner. This work leverages existing frameworks to facilitate the integration offers validation by simulation. A framework for distributed simulation is the IEEE High-Level Architecture (HLA) compliant tool CERTI, which provides the infrastructure for co-simulation of models in various simulation environments as well as hardware components. We use CERTI in combination with Ptolemy II, an environment for modeling and simulating heterogeneous systems. In particular, we focus on models of a CPS, including the physical dynamics of a plant, the software that controls the plant, and the network that enables the communication between controllers. We describe the Ptolemy extensions for the interaction with HLA and demonstrate the approach on a flight control system simulation

NOSQL design for analytical workloads: Variability matters

Big Data has recently gained popularity and has strongly questioned relational databases as universal storage systems, especially in the presence of analytical workloads. As result, co-relational alternatives, commonly known as NOSQL (Not Only SQL) databases, are extensively used for Big Data. As the primary focus of NOSQL is on performance, NOSQL databases are directly designed at the physical level, and consequently the resulting schema is tailored to the dataset and access patterns of the problem in hand. However, we believe that NOSQL design can also benefit from traditional design approaches. In this paper we present a method to design databases for analytical workloads. Starting from the conceptual model and adopting the classical 3-phase design used for relational databases, we propose a novel design method considering the new features brought by NOSQL and encompassing relational and co-relational design altogether.Peer ReviewedPostprint (author's final draft