Connecting the World of Embedded Mobiles: The RIOT Approach to Ubiquitous Networking for the Internet of Things

The Internet of Things (IoT) is rapidly evolving based on low-power compliant protocol standards that extend the Internet into the embedded world. Pioneering implementations have proven it is feasible to inter-network very constrained devices, but had to rely on peculiar cross-layered designs and offer a minimalistic set of features. In the long run, however, professional use and massive deployment of IoT devices require full-featured, cleanly composed, and flexible network stacks. This paper introduces the networking architecture that turns RIOT into a powerful IoT system, to enable low-power wireless scenarios. RIOT networking offers (i) a modular architecture with generic interfaces for plugging in drivers, protocols, or entire stacks, (ii) support for multiple heterogeneous interfaces and stacks that can concurrently operate, and (iii) GNRC, its cleanly layered, recursively composed default network stack. We contribute an in-depth analysis of the communication performance and resource efficiency of RIOT, both on a micro-benchmarking level as well as by comparing IoT communication across different platforms. Our findings show that, though it is based on significantly different design trade-offs, the networking subsystem of RIOT achieves a performance equivalent to that of Contiki and TinyOS, the two operating systems which pioneered IoT software platforms

Putting Instruction Sequences into Effect

An attempt is made to define the concept of execution of an instruction sequence. It is found to be a special case of directly putting into effect of an instruction sequence. Directly putting into effect of an instruction sequences comprises interpretation as well as execution. Directly putting into effect is a special case of putting into effect with other special cases classified as indirectly putting into effect

A Review of Lightweight Thread Approaches for High Performance Computing

High-level, directive-based solutions are becoming the programming models (PMs) of the multi/many-core architectures. Several solutions relying on operating system (OS) threads perfectly work with a moderate number of cores. However, exascale systems will spawn hundreds of thousands of threads in order to exploit their massive parallel architectures and thus conventional OS threads are too heavy for that purpose. Several lightweight thread (LWT) libraries have recently appeared offering lighter mechanisms to tackle massive concurrency. In order to examine the suitability of LWTs in high-level runtimes, we develop a set of microbenchmarks consisting of commonly-found patterns in current parallel codes. Moreover, we study the semantics offered by some LWT libraries in order to expose the similarities between different LWT application programming interfaces. This study reveals that a reduced set of LWT functions can be sufficient to cover the common parallel code patterns andthat those LWT libraries perform better than OS threads-based solutions in cases where task and nested parallelism are becoming more popular with new architectures.The researchers from the Universitat Jaume I de Castelló were supported by project TIN2014-53495-R of the MINECO, the Generalitat Valenciana fellowship programme Vali+d 2015, and FEDER. This work was partially supported by the U.S. Dept. of Energy, Office of Science, Office of Advanced Scientific Computing Research (SC-21), under contract DEAC02-06CH11357. We gratefully acknowledge the computing resources provided and operated by the Joint Laboratory for System Evaluation (JLSE) at Argonne National Laboratory.Peer ReviewedPostprint (author's final draft

GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

FPGA accelerator for gradient boosting decision trees

A decision tree is a well-known machine learning technique. Recently their popularity has increased due to the powerful Gradient Boosting ensemble method that allows to gradually increasing accuracy at the cost of executing a large number of decision trees. In this paper we present an accelerator designed to optimize the execution of these trees while reducing the energy consumption. We have implemented it in an FPGA for embedded systems, and we have tested it with a relevant case-study: pixel classification of hyperspectral images. In our experiments with different images our accelerator can process the hyperspectral images at the same speed at which they are generated by the hyperspectral sensors. Compared to a high-performance processor running optimized software, on average our design is twice as fast and consumes 72 times less energy. Compared to an embedded processor, it is 30 times faster and consumes 23 times less energy

Revisiting Actor Programming in C++

The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model. In this paper, we report on designing and building CAF, the "C++ Actor Framework". CAF targets at providing a concurrent and distributed native environment for scaling up to very large, high-performance applications, and equally well down to small constrained systems. We present the key specifications and design concepts---in particular a message-transparent architecture, type-safe message interfaces, and pattern matching facilities---that make native actors a viable approach for many robust, elastic, and highly distributed developments. We demonstrate the feasibility of CAF in three scenarios: first for elastic, upscaling environments, second for including heterogeneous hardware like GPGPUs, and third for distributed runtime systems. Extensive performance evaluations indicate ideal runtime behaviour for up to 64 cores at very low memory footprint, or in the presence of GPUs. In these tests, CAF continuously outperforms the competing actor environments Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.Comment: 33 page

Deploying RIOT operating system on a reconfigurable Internet of Things end-device

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e ComputadoresThe Internet of Everything (IoE) is enabling the connection of an infinity of physical objects to the Internet, and has the potential to connect every single existing object in the world. This empowers a market with endless opportunities where the big players are forecasting, by 2020, more than 50 billion connected devices, representing an 8 trillion USD market. The IoE is a broad concept that comprises several technological areas and will certainly, include more in the future. Some of those already existing fields are the Internet of Energy related with the connectivity of electrical power grids, Internet of Medical Things (IoMT), for instance, enables patient monitoring, Internet of Industrial Things (IoIT), which is dedicated to industrial plants, and the Internet of Things (IoT) that focus on the connection of everyday objects (e.g. home appliances, wearables, transports, buildings, etc.) to the Internet. The diversity of scenarios where IoT can be deployed, and consequently the different constraints associated to each device, leads to a heterogeneous network composed by several communication technologies and protocols co-existing on the same physical space. Therefore, the key requirements of an IoT network are the connectivity and the interoperability between devices. Such requirement is achieved by the adoption of standard protocols and a well-defined lightweight network stack. Due to the adoption of a standard network stack, the data processed and transmitted between devices tends to increase. Because most of the devices connected are resource constrained, i.e., low memory, low processing capabilities, available energy, the communication can severally decrease the device’s performance. Hereupon, to tackle such issues without sacrificing other important requirements, this dissertation aims to deploy an operating system (OS) for IoT, the RIOT-OS, while providing a study on how network-related tasks can benefit from hardware accelerators (deployed on reconfigurable technology), specially designed to process and filter packets received by an IoT device.O conceito Internet of Everything (IoE) permite a conexão de uma infinidade de objetos à Internet e tem o potencial de conectar todos os objetos existentes no mundo. Favorecendo assim o aparecimento de novos mercados e infinitas possibilidades, em que os grandes intervenientes destes mercados preveem até 2020 a conexão de mais de 50 mil milhões de dispositivos, representando um mercado de 8 mil milhões de dólares. IoE é um amplo conceito que inclui várias áreas tecnológicas e irá certamente incluir mais no futuro. Algumas das áreas já existentes são: a Internet of Energy relacionada com a conexão de redes de transporte e distribuição de energia à Internet; Internet of Medical Things (IoMT), que possibilita a monotorização de pacientes; Internet of Industrial Things (IoIT), dedicada a instalações industriais e a Internet of Things (IoT), que foca na conexão de objetos do dia-a-dia (e.g. eletrodomésticos, wearables, transportes, edifícios, etc.) à Internet. A diversidade de cenários à qual IoT pode ser aplicado, e consequentemente, as diferentes restrições aplicadas a cada dispositivo, levam à criação de uma rede heterogénea composto por diversas tecnologias de comunicação e protocolos a coexistir no mesmo espaço físico. Desta forma, os requisitos chave aplicados às redes IoT são a conectividade e interoperabilidade entre dispositivos. Estes requisitos são atingidos com a adoção de protocolos standard e pilhas de comunicação bem definidas. Com a adoção de pilhas de comunicação standard, a informação processada e transmitida entre dispostos tende a aumentar. Visto que a maioria dos dispositivos conectados possuem escaços recursos, i.e., memória reduzida, baixa capacidade de processamento, pouca energia disponível, o aumento da capacidade de comunicação pode degradar o desempenho destes dispositivos. Posto isto, para lidar com estes problemas e sem sacrificar outros requisitos importantes, esta dissertação pretende fazer o porting de um sistema operativo IoT, o RIOT, para uma solução reconfigurável, o CUTE mote. O principal objetivo consiste na realização de um estudo sobre os benefícios que as tarefas relacionadas com as camadas de rede podem ter ao serem executadas em hardware via aceleradores dedicados. Estes aceleradores são especialmente projetados para processar e filtrar pacotes de dados provenientes de uma interface radio em redes IoT periféricas