267 research outputs found

    Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

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    This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.Siirretty Doriast

    Développement des techniques de test et de diagnostic pour les FPGA hiérarchique de type mesh

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    The evolution trend of shrinking feature size and increasing complexity in modern electronics is being slowed down due to physical limits that generate numerous imperfections and defects during fabrication steps or projected life time of the chip. Field Programmable Gate Arrays (FPGAs) are used in complex digital systems mainly due to their reconfigurability and shorter time-to-market. To maintain a high reliability of such systems, FPGAs should be tested thoroughly for defects. FPGA architecture optimization for area saving and better signal routability is an ongoing process which directly impacts the overall FPGA testability, hence the reliability. This thesis presents a complete strategy for test and diagnosis of manufacturing defects in mesh-based FPGAs containing a novel multilevel interconnects topology which promises to provide better area and routability. Efficiency of the proposed test schemes is analyzed in terms of test cost, respective fault coverage and diagnostic resolution.L’évolution tendant à réduire la taille et augmenter la complexité des circuits électroniques modernes, est en train de ralentir du fait des limitations technologiques, qui génèrent beaucoup de d’imperfections et de defaults durant la fabrication ou la durée de vie de la puce. Les FPGAs sont utilisés dans les systèmes numériques complexes, essentiellement parce qu’ils sont reconfigurables et rapide à commercialiser. Pour garder une grande fiabilité de tels systèmes, les FPGAs doivent être testés minutieusement pour les defaults. L’optimisation de l’architecture des FPGAs pour l’économie de surface et une meilleure routabilité est un processus continue qui impacte directement la testabilité globale et de ce fait, la fiabilité. Cette thèse présente une stratégie complète pour le test et le diagnostique des defaults de fabrication des “mesh-based FPGA” contenant une nouvelle topologie d’interconnections à plusieurs niveaux, ce qui promet d’apporter une meilleure routabilité. Efficacité des schémas proposes est analysée en termes de temps de test, couverture de faute et résolution de diagnostique

    Space Station Freedom data management system growth and evolution report

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    The Information Sciences Division at the NASA Ames Research Center has completed a 6-month study of portions of the Space Station Freedom Data Management System (DMS). This study looked at the present capabilities and future growth potential of the DMS, and the results are documented in this report. Issues have been raised that were discussed with the appropriate Johnson Space Center (JSC) management and Work Package-2 contractor organizations. Areas requiring additional study have been identified and suggestions for long-term upgrades have been proposed. This activity has allowed the Ames personnel to develop a rapport with the JSC civil service and contractor teams that does permit an independent check and balance technique for the DMS

    Addressing Complexity and Intelligence in Systems Dependability Evaluation

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    Engineering and computing systems are increasingly complex, intelligent, and open adaptive. When it comes to the dependability evaluation of such systems, there are certain challenges posed by the characteristics of “complexity” and “intelligence”. The first aspect of complexity is the dependability modelling of large systems with many interconnected components and dynamic behaviours such as Priority, Sequencing and Repairs. To address this, the thesis proposes a novel hierarchical solution to dynamic fault tree analysis using Semi-Markov Processes. A second aspect of complexity is the environmental conditions that may impact dependability and their modelling. For instance, weather and logistics can influence maintenance actions and hence dependability of an offshore wind farm. The thesis proposes a semi-Markov-based maintenance model called “Butterfly Maintenance Model (BMM)” to model this complexity and accommodate it in dependability evaluation. A third aspect of complexity is the open nature of system of systems like swarms of drones which makes complete design-time dependability analysis infeasible. To address this aspect, the thesis proposes a dynamic dependability evaluation method using Fault Trees and Markov-Models at runtime.The challenge of “intelligence” arises because Machine Learning (ML) components do not exhibit programmed behaviour; their behaviour is learned from data. However, in traditional dependability analysis, systems are assumed to be programmed or designed. When a system has learned from data, then a distributional shift of operational data from training data may cause ML to behave incorrectly, e.g., misclassify objects. To address this, a new approach called SafeML is developed that uses statistical distance measures for monitoring the performance of ML against such distributional shifts. The thesis develops the proposed models, and evaluates them on case studies, highlighting improvements to the state-of-the-art, limitations and future work

    Ein flexibles, heterogenes Bildverarbeitungs-Framework fĂĽr weltraumbasierte, rekonfigurierbare Datenverarbeitungsmodule

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    Scientific instruments as payload of current space missions are often equipped with high-resolution sensors. Thereby, especially camera-based instruments produce a vast amount of data. To obtain the desired scientific information, this data usually is processed on ground. Due to the high distance of missions within the solar system, the data rate for downlink to the ground station is strictly limited. The volume of scientific relevant data is usually less compared to the obtained raw data. Therefore, processing already has to be carried out on-board the spacecraft. An example of such an instrument is the Polarimetric and Helioseismic Imager (PHI) on-board Solar Orbiter. For acquisition, storage and processing of images, the instrument is equipped with a Data Processing Module (DPM). It makes use of heterogeneous computing based on a dedicated LEON3 processor in combination with two reconfigurable Xilinx Virtex-4 Field-Programmable Gate Arrays (FPGAs). The thesis will provide an overview of the available space-grade processing components (processors and FPGAs) which fulfill the requirements of deepspace missions. It also presents existing processing platforms which are based upon a heterogeneous system combining processors and FPGAs. This also includes the DPM of the PHI instrument, whose architecture will be introduced in detail. As core contribution of this thesis, a framework will be presented which enables high-performance image processing on such hardware-based systems while retaining software-like flexibility. This framework mainly consists of a variety of modules for hardware acceleration which are integrated seamlessly into the data flow of the on-board software. Supplementary, it makes extensive use of the dynamic in-flight reconfigurability of the used Virtex-4 FPGAs. The flexibility of the presented framework is proven by means of multiple examples from within the image processing of the PHI instrument. The framework is analyzed with respect to processing performance as well as power consumption.Wissenschaftliche Instrumente auf aktuellen Raumfahrtmissionen sind oft mit hochauflösenden Sensoren ausgestattet. Insbesondere kamerabasierte Instrumente produzieren dabei eine große Menge an Daten. Diese werden üblicherweise nach dem Empfang auf der Erde weiterverarbeitet, um daraus wissenschaftlich relevante Informationen zu gewinnen. Aufgrund der großen Entfernung von Missionen innerhalb unseres Sonnensystems ist die Datenrate zur Übertragung an die Bodenstation oft sehr begrenzt. Das Volumen der wissenschaftlich relevanten Daten ist meist deutlich kleiner als die aufgenommenen Rohdaten. Daher ist es vorteilhaft, diese bereits an Board der Sonde zu verarbeiten. Ein Beispiel für solch ein Instrument ist der Polarimetric and Helioseismic Imager (PHI) an Bord von Solar Orbiter. Um die Daten aufzunehmen, zu speichern und zu verarbeiten, ist das Instrument mit einem Data Processing Module (DPM) ausgestattet. Dieses nutzt ein heterogenes Rechnersystem aus einem dedizierten LEON3 Prozessor, zusammen mit zwei rekonfigurierbaren Xilinx Virtex-4 Field-Programmable Gate Arrays (FPGAs). Die folgende Arbeit gibt einen Überblick über verfügbare Komponenten zur Datenverarbeitung (Prozessoren und FPGAs), die den Anforderungen von Raumfahrtmissionen gerecht werden, und stellt einige existierende Plattformen vor, die auf einem heterogenen System aus Prozessor und FPGA basieren. Hierzu gehört auch das Data Processing Module des PHI Instrumentes, dessen Architektur im Verlauf dieser Arbeit beschrieben wird. Als Kernelement der Dissertation wird ein Framework vorgestellt, das sowohl eine performante, als auch eine flexible Bilddatenverarbeitung auf einem solchen System ermöglicht. Dieses Framework besteht aus verschiedenen Modulen zur Hardwarebeschleunigung und bindet diese nahtlos in den Datenfluss der On-Board Software ein. Dabei wird außerdem die Möglichkeit genutzt, die eingesetzten Virtex-4 FPGAs dynamisch zur Laufzeit zu rekonfigurieren. Die Flexibilität des vorgestellten Frameworks wird anhand mehrerer Fallbeispiele aus der Bildverarbeitung von PHI dargestellt. Das Framework wird bezüglich der Verarbeitungsgeschwindigkeit und Energieeffizienz analysiert

    On Dynamic Monitoring Methods for Networks-on-Chip

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    Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.Siirretty Doriast

    Network-on-Chip

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    Limitations of bus-based interconnections related to scalability, latency, bandwidth, and power consumption for supporting the related huge number of on-chip resources result in a communication bottleneck. These challenges can be efficiently addressed with the implementation of a network-on-chip (NoC) system. This book gives a detailed analysis of various on-chip communication architectures and covers different areas of NoCs such as potentials, architecture, technical challenges, optimization, design explorations, and research directions. In addition, it discusses current and future trends that could make an impactful and meaningful contribution to the research and design of on-chip communications and NoC systems

    Run-time management of many-core SoCs: A communication-centric approach

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    The single core performance hit the power and complexity limits in the beginning of this century, moving the industry towards the design of multi- and many-core system-on-chips (SoCs). The on-chip communication between the cores plays a criticalrole in the performance of these SoCs, with power dissipation, communication latency, scalability to many cores, and reliability against the transistor failures as the main design challenges. Accordingly, we dedicate this thesis to the communicationcentered management of the many-core SoCs, with the goal to advance the state-ofthe-art in addressing these challenges. To this end, we contribute to on-chip communication of many-core SoCs in three main directions. First, we start with a synthesizable SoC with full system simulation. We demonstrate the importance of the networking overhead in a practical system, and propose our sophisticated network interface (NI) that offloads the work from SW to HW. Our results show around 5x and up to 50x higher network performance, compared to previous works. As the second direction of this thesis, we study the significance of run-time application mapping. We demonstrate that contiguous application mapping not only improves the network latency (by 23%) and power dissipation (by 50%), but also improves the system throughput (by 3%) and quality-of-service (QoS) of soft real-time applications (up to 100x less deadline misses). Also our hierarchical run-time application mapping provides 99.41% successful mapping when up to 8 links are broken. As the final direction of the thesis, we propose a fault-tolerant routing algorithm, the maze-routing. It is the first-in-class algorithm that provides guaranteed delivery, a fully-distributed solution, low area overhead (by 16x), and instantaneous reconfiguration (vs. 40K cycles down time of previous works), all at the same time. Besides the individual goals of each contribution, when applicable, we ensure that our solutions scale to extreme network sizes like 12x12 and 16x16. This thesis concludes that the communication overhead and its optimization play a significant role in the performance of many-core SoC
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