152 research outputs found

    DeSyRe: on-Demand System Reliability

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    The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

    Low-Power Embedded Design Solutions and Low-Latency On-Chip Interconnect Architecture for System-On-Chip Design

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    This dissertation presents three design solutions to support several key system-on-chip (SoC) issues to achieve low-power and high performance. These are: 1) joint source and channel decoding (JSCD) schemes for low-power SoCs used in portable multimedia systems, 2) efficient on-chip interconnect architecture for massive multimedia data streaming on multiprocessor SoCs (MPSoCs), and 3) data processing architecture for low-power SoCs in distributed sensor network (DSS) systems and its implementation. The first part includes a low-power embedded low density parity check code (LDPC) - H.264 joint decoding architecture to lower the baseband energy consumption of a channel decoder using joint source decoding and dynamic voltage and frequency scaling (DVFS). A low-power multiple-input multiple-output (MIMO) and H.264 video joint detector/decoder design that minimizes energy for portable, wireless embedded systems is also designed. In the second part, a link-level quality of service (QoS) scheme using unequal error protection (UEP) for low-power network-on-chip (NoC) and low latency on-chip network designs for MPSoCs is proposed. This part contains WaveSync, a low-latency focused network-on-chip architecture for globally-asynchronous locally-synchronous (GALS) designs and a simultaneous dual-path routing (SDPR) scheme utilizing path diversity present in typical mesh topology network-on-chips. SDPR is akin to having a higher link width but without the significant hardware overhead associated with simple bus width scaling. The last part shows data processing unit designs for embedded SoCs. We propose a data processing and control logic design for a new radiation detection sensor system generating data at or above Peta-bits-per-second level. Implementation results show that the intended clock rate is achieved within the power target of less than 200mW. We also present a digital signal processing (DSP) accelerator supporting configurable MAC, FFT, FIR, and 3-D cross product operations for embedded SoCs. It consumes 12.35mW along with 0.167mm2 area at 333MHz

    Test-Delivery Optimization in Manycore SOCs

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    We present two test-data delivery optimization algorithms for system-on-chip (SOC) designs with hundreds of cores, where a network-on-chip (NOC) is used as the interconnection fabric. We first present an e ective algorithm based on a subsetsum formulation to solve the test-delivery problem in NOCs with arbitrary topology that use dedicated routing. We further propose an algorithm for the important class of NOCs with grid topology and XY routing. The proposed algorithm is the first to co-optimize the number of access points, access-point locations, pin distribution to access points, and assignment of cores to access points for optimal test resource utilization of such NOCs. Testtime minimization is modeled as an NOC partitioning problem and solved with dynamic programming in polynomial time. Both the proposed methods yield high-quality results and are scalable to large SOCs with many cores. We present results on synthetic grid topology NOC-based SOCs constructed using cores from the ITC’02 benchmark, and demonstrate the scalability of our approach for two SOCs of the future, one with nearly 1,000 cores and the other with 1,600 cores. Test scheduling under power constraints is also incorporated in the optimization framework

    Effective power saving method by on-chip traffic compression in noc-based embedded systems

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    [EN] of components, relying on an efficient on-chip network (network-on-chip; NoC). As the size of the system increases, NoC performance and power consumption become a central issue. In this project, we design compression strategies at the NoC level reducing the number of transmitted flits and consequently the energy consumed. The provided mechanism relies on the abundance of memory data blocks filled with zeros in the analysed applications, thus easily compressible by using a zero-elimination strategy. We provide a hardware implementation for both compression and decompression end points at a generic network interface (NI). The mechanisms have been designed in isolated mode in order to make them modular and easily adapted to any NI protocol. Results show the effectiveness of the compression and decompression mechanisms and the low overhead they introduce. The percentage of traffic reduced by the compression strategy (it is reduced by a factor of 3) justifies the added resources. This work reflects some parts of the main research directions we tackle in the wider PhD framework. In particular, we propose a method for power efficient memory traffic management. The work presented here represents the initial research directions in simulation development, traffic pattern characterization and initial solutions development[ES] Con los avances de la tecnología, los sistemas en chip multiprocesador (MPSoC) aumentan en número de componentes, apoyándose en una red en el chip (NoC) eficiente. Según crece el tamaño de estos sistemas, la eficiencia de la red tanto temporal como energética se convierte en una parte primordial. En este proyecto diseñamos estrategias de compresión a nivel de red (en la NoC) reduciendo el número de flits transmitidos y por tanto la energía consumida. El método propuesto se basa en la abundancia de bloques de memoria con largas cadenas de ceros que se detectaron en las aplicaciones analizadas. Esta abundancia de ceros facilita la compresión mediante estrategias de eliminación de ceros. Ofrecemos una implementación hardware tanto de la parte de compresión como de la de descompresión sobre un interfaz de red (NI) genérico. Los mecanismos propuestos han sido diseñados de forma aislada para hacerlos modulares y fácilmente adaptables a cualquier protocolo de NI. Los resultados muestran la efectividad de los mecanismos de compresión y descompresión y la escasa penalización que introducen. El porcentaje de tráfico reducido mediante la estrategia de compresión (se reduce con un factor de 3) justifica los recursos extra requeridos. Este trabajo refleja parte de la línea de investigación global que se pretende abordar en el marco más amplio de un doctorado. En particular proponemos un método de gestión del tráfico de memoria energéticamente eficiente. El trabajo presentado aquí representa pues una primera aproximación a la investigación realizando un desarrollo parcial del simulador, caracterización de patrones de tráfico y el desarrollo de una solución parcialSoler Heredia, M. (2013). Effective power saving method by on-chip traffic compression in noc-based embedded systems. http://hdl.handle.net/10251/43774Archivo delegad

    DeSyRe: On-demand system reliability

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    The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect-/fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints. (C) 2013 Elsevier B.V. All rights reserved

    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

    Circuits and Systems Advances in Near Threshold Computing

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    Modern society is witnessing a sea change in ubiquitous computing, in which people have embraced computing systems as an indispensable part of day-to-day existence. Computation, storage, and communication abilities of smartphones, for example, have undergone monumental changes over the past decade. However, global emphasis on creating and sustaining green environments is leading to a rapid and ongoing proliferation of edge computing systems and applications. As a broad spectrum of healthcare, home, and transport applications shift to the edge of the network, near-threshold computing (NTC) is emerging as one of the promising low-power computing platforms. An NTC device sets its supply voltage close to its threshold voltage, dramatically reducing the energy consumption. Despite showing substantial promise in terms of energy efficiency, NTC is yet to see widescale commercial adoption. This is because circuits and systems operating with NTC suffer from several problems, including increased sensitivity to process variation, reliability problems, performance degradation, and security vulnerabilities, to name a few. To realize its potential, we need designs, techniques, and solutions to overcome these challenges associated with NTC circuits and systems. The readers of this book will be able to familiarize themselves with recent advances in electronics systems, focusing on near-threshold computing
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