Exploring manycore architectures for next-generation HPC systems through the MANGO approach

[EN] The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High-Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit customization to adapt computing resources to reach the desired QoS. For this purpose, it explores different but interrelated mechanisms across the architecture and system software. In particular, in this paper we focus on the runtime resource management, the thermal management, and support provided for parallel programming, as well as introducing three applications on which the project foreground will be validated.This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 671668.Flich Cardo, J.; Agosta, G.; Ampletzer, P.; Atienza-Alonso, D.; Brandolese, C.; Cappe, E.; Cilardo, A.... (2018). Exploring manycore architectures for next-generation HPC systems through the MANGO approach. Microprocessors and Microsystems. 61:154-170. https://doi.org/10.1016/j.micpro.2018.05.011S1541706

Dimensionnement et Qualité de Service pour les systèmes à criticité mixte dans les architectures embarquées à base de Network on Chip (NoC)

L'évolution de Systems-on-Chip (SoCs) est rapide et le nombre des processeurs augmente conduisant à la transition des les plates-formes Multi-core vers les Manycore. Dans telles plates-formes, l'architecture d'interconnexion a également décalé des bus traditionnels vers les Réseaux sur puce (NoC) afin de faire face à la mise en échelle. Les NoC permettent aux processeurs d'échanger des informations avec la mémoire et les périphériques lors de l'exécution d'une tâche et d'effectuer plusieurs communications en parallèle. Les plates-formes basées sur un NoC sont aussi présentes dans des systèmes embarqués, caractérisés par des exigences comme la prédictibilité, la sécurité et la criticité mixte. Afin de fournir telles fonctionnalités dans les plates-formes commerciales existantes, il faut prendre en considération le NoC qui est un élément clé ayant un impact important sur les performances d'un SoC. Une tâche échange des informations à travers du NoC et par conséquent, son temps d'exécution dépend du temps de transmission des flux qu'elle génère. En calculant le temps de transmission de pire cas (WCTT) des flux dans le NoC, une étape est faite vers le calcul du temps d'exécution de pire cas (WCET) d'une tâche. Ceci contribue à la prédictibilité globale du système. De plus, en prenant en compte les politiques d'arbitrage dans le NoC, il est possible de fournir des garanties de sécurité contre des tâches compromises qui pourraient essayer de saturer les ressources du système (attaque DoS). Dans les systèmes critiques de sécurité, une distinction des tâches par rapport à leur niveau de criticité, permet aux tâches de criticité mixte de coexister et d'exécuter en harmonie. De plus, ça permet aux tâches critiques de maintenir leurs temps d'exécution au prix de tâches de faible criticité qui seront ralenties ou arrêtées. Cette thèse vise à fournir des méthodes et des mécanismes dans le but de contribuer aux axes de prédictibilité, de sécurité et de criticité mixte dans les architectures Manycore basées sur Noc. En outre, l'incitation consiste à relever conjointement les défis dans ces trois axes en tenant compte de leur impact mutuel. Chaque axe a été étudié individuellement, mais très peu de recherche prend en compte leur interdépendance. Cette fusion des aspects est de plus en plus intrinsèque dans des domaines tels que Internet-of-Things, Cyber-Physical Systems (CPS), véhicules connectés et autonomes qui gagnent de l'élan. La raison en est leur haut degré de connectivité qui crée une grande surface d'exposition ainsi que leur présence croissante qui rend l'impact des attaques sévère et visible. Les contributions de cette thèse consistent en une méthode pour fournir une prédictibilité aux flux dans le NoC, un mécanisme pour la sécurité du NoC et une boîte à outils pour la génération de trafic utilisée pour l'analyse comparative. La première contribution est une adaptation de l'approche de la trajectoire traditionnellement utilisée dans les réseaux avioniques (AFDX) pour calculer le WCET. Dans cette thèse, nous identifions les différences et les similitudes dans l'architecture NoC et modifions l'approche de la trajectoire afin de calculer le WCTT des flux NoC. La deuxième contribution est un mécanisme qui permet de détecter les attaques de DoS et d'atténuer leur impact dans un ensemble des flux de criticité mixte. Plus précisément, un mécanisme surveille le NoC et lors de la détection d'un comportement anormal, un deuxième mécanisme d'atténuation s'active. Ce dernier applique des limites de trafic à la source et restreint le taux auquel le NoC est occupé. Cela atténuera l'impact de l'attaque, garantissant la disponibilité des ressources pour les tâches de haute criticité. Finalement NTGEN, est un outil qui peut générer automatiquement des jeux des flux aléatoires mais qui provoquent une occupation NoC prédéterminée. Ces ensembles sont ensuite injectés dans le NoC et les informations sont collectées en fonction de la latenceThe evolution of Systems-on-Chip (SoCs) is rapid and the number of processors has increased transitioning from Multi-core to Manycore platforms. In such platforms, the interconnect architecture has also shifted from traditional buses to Networks-on-Chip (NoC) in order to cope with scalability. NoCs allow the processors to exchange information with memory and peripherals during task execution and enable multiple communications in parallel. NoC-based platforms are also present in embedded systems, characterized by requirements like predictability, security and mixed-criticality. In order to enable such features in existing commercial platforms it is necessary to take into consideration the NoC which is a key element with an important impact to a SoC's performance. A task exchanges information through the NoC and as a result, its execution time depends on the transmission time of the flows it generates. By calculating the Worst Case Transmission Time (WCTT) of flows in the NoC, a step is made towards the calculation of the Worst Case Execution Time (WCET) of a task. This contributes to the overall predictability of the system. Similarly by leveraging arbitration and traffic policies in the NoC it is possible to provide security guarantees against compromised tasks that might try to saturate the system's resources (DoS attack). In safety critical systems, a distinction of tasks in relation to their criticality level, allows tasks of mixed criticality to co-exist and execute in harmony. In addtition, it allows critical tasks to maintain their execution times at the cost of tasks of lower criticality that will be either slowed down or stopped. This thesis aims to provide methods and mechanisms with the objective to contribute in the axes of predictability, security and mixed criticality in NoC-based Manycore architectures. In addition, the incentive is to jointly address the challenges in these three axes taking into account their mutual impact. Each axis has been researched individually, but very little research takes under consideration their interdependence. This fusion of aspects is becoming more and more intrinsic in fields like the Internet-of-Things, Cyber-Physical Systems (CPSs), connected and autonomous vehicles which are gaining momentum. The reason being their high degree of connectivity which is creates great exposure as well as their increasing presence which makes attacks severe and visible. The contributions of this thesis consist of a method to provide predictability to a set of flows in the NoC, a mechanism to provide security properties to the NoC and a toolkit for traffic generation used for benchmarking. The first contribution is an adaptation of the trajectory approach traditionally used in avionics networks (AFDX) to calculate WCET. In this thesis, we identify the differences and similarities in NoC architecture and modify the trajectory approach in order to calculate the WCTT of NoC flows. The second contribution is a mechanism that detects DoS attacks and mitigates their impact in a mixed criticality set of flows. More specifically, a monitor mechanism will detect abnormal behavior, and activate a mitigation mechanism. The latter, will apply traffic shaping at the source and restrict the rate at which the NoC is occupied. This will limit the impact of the attack, guaranteeing resource availability for high criticality tasks. Finally NTGEN, is a toolkit that can automatically generate random sets of flows that result to a predetermined NoC occupancy. These sets are then injected in the NoC and information is collected related to latenc

Deterministic scheduling in Networks-on-Chip using the Trajectory approach

International audience—In this paper, we consider the problem of guaranteeing real-time end-to-end transmission time for flows sent on a Network-on-Chip (NoC) with First-in First-out (FIFO) scheduling on each node. We show how to adapt the Trajectory approach, used in the context of Avionics Full DupleX switched Ethernet (AFDX) networks to characterize end-to-end transmission delays, to the context of NoC-based Systems-on-Chip (SoCs). We characterize the benefit of the Trajectory approach on an example

A mixed criticality approach for the security of critical flows in a network-on-chip

International audienc

Retour au sport après reconstruction du ligament croisé antérieur

Despite continuous advances in techniques for anterior cruciate ligament reconstruction (ACLR), return to play (RTP) after surgery remains a challenge. More than one-third of the patients are unable to return to their preinjury sport level, for most because of a fear to sustain another injury. And when a RTP is attempted, up to 20% will tear their graft and a similar % will sustain an ACL tear on the opposite side. We believe that these failures result from an incomplete recovery. Based on a literature review and on our experience, we suggest 6 objective criteria to allow a safer RTP. They rely on laxity, strength, neuromuscular function, and psychological evaluations. Rehabilitation after ACLR should focus on the deficits identified by these tests and on they specific needs of the sport that the athlete plans to return to

5G-ENSURE - D3.1 5G-PPP security enablers technical roadmap (early vision)

This document provides an early vision (at M4) of the 5G security and privacy enablers proposed by the 5G-ENSURE project, and that are planned to be developed through two major releases: v1.0 (R1) due at M11/Sep’16 and v2.0 (R2) due at M22/Aug’17. It details the Technical Roadmap for v1.0 (R1) in terms of enablers in scope and their features, while providing insights for v2.0 (R2) enablers that will be fully detailed in an update of this deliverable (D3.5 due at M13/Nov’16) taking account of the progress and achievements made by that time. Enablers envisioned are here presented organized in categories, which represent major security areas recognized as topmost priorities for 5G-PPP & 5G Security: Authentication, Authorization and Accountability (AAA); Privacy; Trust; Security Monitoring and Network management & virtualization isolation. They are also presented following a common template covering each of the following key aspects: product vision, technology area, security aspects, security challenges, technical roadmap for first release vs. next release.In the AAA category the main focus is on 5G users’ authentication, authorization and accounting, but the contribution of the AAA enablers goes beyond the incremental improvements to security that one would expect in a next-generation network. The evolving 5G network will support an unpredictable number of devices due to the boom of Internet of Things (IoT), whose security these enablers will aim to address. Moreover, the enablers target to integrate authentication and authorization functions between satellite and terrestrial systems.The main objective of the 5G-Ensure Privacy enablers is to identify in advance 5G user privacy requirements and to provide security mechanisms able to prevent privacy violations by adopting a proactive, privacy-by-design approach. For each 5G use case, the privacy mitigation technology (e.g., anonymity by using temporary identity, access control mechanisms, new encryption system and procedures, etc.) was also investigated so as to satisfy privacy requirements. The privacy enablers aim to enhance user data protection by proposing solutions at several layers: at the network layer, as well as application layer, i.e., privacy as a service.The Trust category will provide trust models which will address the complex relationships between the many actors in 5G networks including the machine-to-machine interactions characterising the next generation networks. The trust model needs to address the different aspects of trust, between automated systems (M2Mt), between human stakeholders holding responsibilities for different parts of 5G networks, between user and network operators and between users of the network (U2Ut), trust that a human stakeholder has towards a system (U2Mt), that an automated system (machine) has in users that it interacts with.5G-ENSURE project also aims at providing new innovative solutions ensuring the highest level of security and resilience in 5G network. Mobile networks will dramatically evolve with the fifth generation of networks compared to 3/4G, in particular with new concepts and technologies such Internet of Things, infrastructure virtualization (SDN, NFV), network resource sharing, new access interfaces, dynamic network topologies, slicing and so forth. These technologies introduce new security and resilience and provide new opportunities to implement extensive and accurate security solutions. Thus, new innovative approaches to predict and counter these challenges will be considered by the category devoted to Monitoring the 5G security

MANGO: Exploring Manycore Architectures for Next-GeneratiOn HPC Systems

The Horizon 2020 MANGO project aims at exploring deeply heterogeneous accelerators for use in High-Performance Computing systems running multiple applications with different Quality of Service (QoS) levels. The main goal of the project is to exploit customization to adapt computing resources to reach the desired QoS. For this purpose, it explores different but interrelated mechanisms across the architecture and system software. In particular, in this paper we focus on the runtime resource management, the thermal management, and support provided for parallel programming, as well as introducing three applications on which the project foreground will be validated