Caractérisation automatisée de la consommation de puissance des processeurs pour l'estimation au niveau système

RÉSUMÉ De nos jours, la consommation de puissance est une contrainte clé et une métrique de performance essentielle lors du design des systèmes numériques. La dissipation de chaleur excessive sur les circuits intégrés diminue relativement leurs performances. Également, plus que jamais, nous avons le besoin d’augmenter le temps de vie des batteries de nouvelles électroniques portables. Avec les techniques de design classiques, RTL « Register Transfer Level », une estimation de puissance précise est possible seulement aux dernières étapes du processus de développement. Pour remédier à cette problématique, on a récemment proposé dans la littérature de hausser le niveau d’abstraction de la conception de systèmes embarqués à l’aide de la méthodologie de niveau système « Electronic System Level » (ESL). Dans cette perspective, ce travail propose une méthodologie capable de caractériser automatiquement la consommation de puissance des processeurs configurable de type « soft-processors » et de générer un modèle efficace pour l’estimation de l’énergie consommée au niveau système. À l'aide de ce modèle, une étude comparative entre trois techniques d’estimation est donc présentée. Les résultats de cinq programmes tests montrent une estimation de puissance huit mille fois plus rapide que les techniques d’estimation conventionnelles et une erreur moyenne de seulement ±3.98 % pour le processeur LEON3 et de ±10.70 % pour le processeur Microblaze.----------ABSTRACT Nowadays, power consumption is a key constraint and a digital system design essential metric of performance. Excessive heat dissipation of integrated circuits relatively decreases the performance of the system. Also, more than ever, we need to increase the battery lifetime of new portable electronics. With classical design techniques as RTL « Register Transfer Level », precise power estimation is only possible in the final stages of the development process. To solve this problem, the literature recently proposed to raise the abstraction level of embedded systems design, using ESL « Electronic System Level » methodology. In this context, this project proposes a methodology to automatically characterize configurable soft-processors power consumption and generate an effective power model for energy consumption estimation at system level. Using this model, a comparative study between three estimation techniques is also presented. The results of five benchmarks show that our power estimation is eight thousand times faster than conventional estimation techniques and an average error of only ±3.98 % for the LEON3 processor and ±10.70 % for the Microblaze processor

Energy/power consumption model for an embedded processor board

This dissertation, whose research has been conducted at the Group of Electronic and Microelectronic Design (GDEM) within the framework of the project Power Consumption Control in Multimedia Terminals (PCCMUTE), focuses on the development of an energy estimation model for the battery-powered embedded processor board. The main objectives and contributions of the work are summarized as follows: A model is proposed to obtain the accurate energy estimation results based on the linear correlation between the performance monitoring counters (PMCs) and energy consumption. the uniqueness of the appropriate PMCs for each different system, the modeling methodology is improved to obtain stable accuracies with slight variations among multiple scenarios and to be repeatable in other systems. It includes two steps: the former, the PMC-filter, to identify the most proper set among the available PMCs of a system and the latter, the k-fold cross validation method, to avoid the bias during the model training stage. The methodology is implemented on a commercial embedded board running the 2.6.34 Linux kernel and the PAPI, a cross-platform interface to configure and access PMCs. The results show that the methodology is able to keep a good stability in different scenarios and provide robust estimation results with the average relative error being less than 5%. Este trabajo fin de máster, cuya investigación se ha desarrollado en el Grupo de Diseño Electrónico y Microelectrónico (GDEM) en el marco del proyecto PccMuTe, se centra en el desarrollo de un modelo de estimación de energía para un sistema empotrado alimentado por batería. Los objetivos principales y las contribuciones de esta tesis se resumen como sigue: Se propone un modelo para obtener estimaciones precisas del consumo de energía de un sistema empotrado. El modelo se basa en la correlación lineal entre los valores de los contadores de prestaciones y el consumo de energía. Considerando la particularidad de los contadores de prestaciones en cada sistema, la metodología de modelado se ha mejorado para obtener precisiones estables, con ligeras variaciones entre escenarios múltiples y para replicar los resultados en diferentes sistemas. La metodología incluye dos etapas: la primera, filtrado-PMC, que consiste en identificar el conjunto más apropiado de contadores de prestaciones de entre los disponibles en un sistema y la segunda, el método de validación cruzada de K iteraciones, cuyo fin es evitar los sesgos durante la fase de entrenamiento. La metodología se implementa en un sistema empotrado que ejecuta el kernel 2.6.34 de Linux y PAPI, un interfaz multiplataforma para configurar y acceder a los contadores. Los resultados muestran que esta metodología consigue una buena estabilidad en diferentes escenarios y proporciona unos resultados robustos de estimación con un error medio relativo inferior al 5%

Gate-level power estimation using tagged probabilistic simulation

In this paper, we present a probabilistic! simulation technique to estimate the power consumption of a CMOS circuit under a general delay model. This technique is based on the notion of a tagged (probability) waveform, which models the set of all possible events at the output of each circuit node. Tagged waveforms are obtained by partitioning the logic waveform space of a circuit node according to the initial and final values of each logic waveform and compacting all logic waveforms in each partition by a single tagged waveform. To improve the efficiency of tagged probabilistic simulation, only tagged waveforms at the circuit inputs are exactly computed. The tagged waveforms of the remaining nodes are computed using a compositional scheme that propagates the tagged waveforms from circuit inputs to circuit outputs. We obtain significant speed up over explicit simulation methods with an average error of only 6\%. This also represents a factor of 2-3x improvement in accuracy of power estimates over previous probabilistic simulation approaches