Aliénor Richard

A framework introducing model reversibility in SoC design space exploration

In this paper we present a general framework for the support of flexible models representation and execution in the context of SoC design space exploration. Coming as a C++ library, it allows the user to gather models from its own and existing models into larger and more complete models. Compared to existing modeling systems we introduce the notion of model reversibility that allows the user to turn any parameter appearing in a model into the output : it increases the model flexibility and enables its reuse in very different problems. Aside from providing specification and execution support, the framework also permits dynamic model sensitivity analysis and efficient parameter sensitivity analysis for closed-formed models. Through this paper we explain our original 3-level hierarchical representation of model and explain meanwhile how it offers flexibility and model robustness using a XML schema grammar.

A Multi-objective and Hierarchical Exploration Tool for SoC Performance Estimation

In this paper we present a flexible performance estimation tool called Nessie developed to provide system-on-chip designers with automated multi-objective design space exploration and its related tool called Yeti building and executing reusable closed-formed models. After reviewing the existing closed-formed expressions based and application/platform mapping performance estimation tools, we propose an hybrid tool to cope with their limitations. We present a brief summary of the functionalities of Yeti and describe Nessie, our hierarchical application/platform performance estimation mapping tool which banalizes all the degrees of freedom for in-depth design space exploration and introduces multi-objective modeling. Through this paper, we explain how the combination of these tools provides the designer with innovative and powerful functionalities for performance prediction at the earlier stages of the design flow.

Development and validation of Nessie: a multi-criteria performance estimation tool for SoC

The paper presents Nessie [1], an original multicriteria exploration tool able to decide on functional and nonfunctional aspects of SoCs based on the application and platform descriptions and the costs (energy, execution time, area, ...). Indeed, the different performance prediction tools we can find in the literature, aiming at helping designers to take decisions and find efficient solutions, have some limitations that we wanted to overcome. To validate our tool, we have chosen real case study. In particular, we present here an example based on a 3MF MPSoC platform executing a real time AVC/H.264 video decoding extended to 3D-stacked architectures. Results given by Nessie, based on the average wire power consumption, have reinforced us in the utility of such a tool to help designers to take decision, especially in huge design spaces like embedded SoC ones.