Interruption (informatique)

Résumé

En informatique, une interruption est une suspension temporaire de l'exécution d'un programme informatique par le microprocesseur afin d'exécuter un programme prioritaire (appelé service d'interruption). : avancement d'une horloge, signalisation de la complétion d'un transfert de données, positionnement d'une tête de lecture/écriture Cependant, on l'utilise aussi pour désigner des exceptions, c'est-à-dire des arrêts provoqués par une condition exceptionnelle dans le programme (instruction erronée, accès à une zone mémoire inexistante, calcul arithmétique incorrect, appel volontaire au système d'exploitation). On parle alors parfois d'interruptions asynchrones pour désigner celles résultant d'un événement externe, et d'interruptions synchrones pour désigner les exceptions provoquées par le déroulement du programme. . Fonctionnement Lors d'une interruption, le processeur enregistre tout ou une partie de son état interne, généralement dans la pile système, et exécute ensuit

Source officielle

https://fr.wikipedia.org/wiki/Interruption_(informatique)

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Asynchronous Broadcast on the Intel SCC using Interrupts

Darko Petrovic, Thomas Ropars, André Schiper, Omid Shahmirzadi

This paper focuses on the design of an asynchronous broadcast primitive on the Intel SCC. Our solution is based on OC-Bcast, a state-of-the-art k-ary tree synchronous broadcast algorithm that leverages the parallelism provided by on-chip Remote Memory Accesses to Message Passing Buffers. In the paper, we study the use of parallel inter-core interrupts as a means to implement an efficient asynchronous group communication primitive, and present the userspace library we designed to be able to use interrupts in OC-Bcast and make it work asynchronously. Our experimental evaluation shows that our algorithm allows parallel broadcast operations to efficiently progress concurrently and provides low latency for a single broadcast operation. It highlights that parallel interrupts can help implementing efficient group communication primitives on many-core systems.

2012

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We developed a prototype for measuring physiological data for pulse transit time (PTT) estimation that will be used for ambulatory blood pressure (BP) monitoring. The device is comprised of an embedded system with multimodal sensors that streams high-throughput data to a custom Android application. The primary focus of this paper is on the hardware–software codesign that we developed to address the challenges associated with reliably recording data over Bluetooth on a resource-constrained platform. In particular, we developed a lossless compression algorithm that is based on optimally selective Huffman coding and Huffman prefixed coding, which yields virtually identical compression ratios to the standard algorithm, but with a 67–99% reduction in the size of the compression tables. In addition, we developed a hybrid software–hardware flow control method to eliminate microcontroller (MCU) interrupt-latency related data loss when multi-byte packets are sent from the phone to the embedded system via a Bluetooth module at baud rates exceeding 115,200 bit/s. The empirical error rate obtained with the proposed method with the baud rate set to 460,800 bit/s was identically equal to 0%. Our robust and computationally efficient physiological data acquisition system will enable field experiments that will drive the development of novel algorithms for PTT-based continuous BP monitoring.

2020

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In reinforcement learning, agents learn by performing actions and observing their outcomes. Sometimes, it is desirable for a human operator to \textit{interrupt} an agent in order to prevent dangerous situations from happening. Yet, as part of their learning process, agents may link these interruptions, that impact their reward, to specific states and deliberately avoid them. The situation is particularly challenging in a multi-agent context because agents might not only learn from their own past interruptions, but also from those of other agents. Orseau and Armstrong~\cite{orseau2016safely} defined \emph{safe interruptibility} for one learner, but their work does not naturally extend to multi-agent systems. This paper introduces \textit{dynamic safe interruptibility}, an alternative definition more suited to decentralized learning problems, and studies this notion in two learning frameworks: \textit{joint action learners} and \textit{independent learners}. We give realistic sufficient conditions on the learning algorithm to enable dynamic safe interruptibility in the case of joint action learners, yet show that these conditions are not sufficient for independent learners. We show however that if agents can detect interruptions, it is possible to prune the observations to ensure dynamic safe interruptibility even for independent learners.

EPFL2017

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