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The TULIPP project aims to simplify development of embedded vision applications with low-power and real-time requirements by providing a complete image processing system package called the TULIPP Starter Kit. To achieve this, the chosen high-performance embedded vision platform needs to be extended with performance analysis and power measurement features. The lack of such features plagues most embedded vision platforms in general and practitioners have adopted adhoc methods to circumvent the problem. In this paper, we describe four generic utilities that complement and refine the capabilities of existing platforms for embedded vision applications. Concretely, we describe a novel power measurement and analysis utility, a platform-optimized image processing library, a dynamic partial reconfiguration utility, and an utility providing support for using the real-time OS HIPPEROS within Xilinx SDSoC. Collectively, these utilities enable efficient development of image processing applications on the TULIPP hardware platform. In future work, we will evaluate the relative benefit of these utilities on key embedded image processing metrics such as frame rate and power consumption.

Fault Tolerance is an increasing challenge for integrated circuits due to semiconductor technology scaling. This paper looks at how artificial evolution may be tuned to the creation of novel redundancy structures which may be applied to meet this challenge. However, as these structures are unknown it is a challenge in itself to tune evolution to create them. As such, no solution has yet been found. This paper provides a discussion about the issues addressed and experiments conducted and thus provides an overview of the lessons learned in this work.

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