The design requirements of modern applications that target embedded systems, such as the need for high performance and low energy consumption, impose challenges on developers. Software tools capable of providing performance and energy consumption estimations are useful for addressing these challenges. Such tools aim to reduce development time and alleviate the time-to-market pressure. In this work, we propose a flexible tool that enables the estimation of performance and energy consumption of the application on embedded devices, providing a complete methodology based on which the user can add estimation models for various platforms. In contrast to existing tools that either rely on dynamic instrumentation or require detailed modeling of the hardware, the proposed tool leverages static analysis techniques applied at instruction level coupled with data-driven regression models. The proposed method is tested using a widely used benchmark suite for evaluation.
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