Frames-to-AER efficiency study based on CPUs performance counters

Image processing in digital computer systems usually considers the visual information as a sequence of frames. These frames are from photographs that capture reality for a short period of time. They are renewed and transmitted at a rate of 25-30 frames per second, in a typical real-time scenario. Each of these frames needs to be filtered and processed in order to detect a feature on it. This processing is usually based on very expensive operations in terms of resource consumption (processor resources and processing time) for an efficient real-time application. In contrast, neuro-inspired systems, which work in a manner similar to the nervous system, may resolve those and others more complex problems, such as visual recognition in real-time. The spike-based philosophy for visual information processing based on the neuro-inspired Address-Event-Representation (AER) is achieving nowadays very high performances. Address-Event-Representation (AER) is a neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge numbers of neurons located on different chips. When building multi-chip muti-layered AER systems it is absolutely necessary to have a computer interface that allows (a) to read AER interchip traffic into the computer and visualize it on screen, and (b) convert conventional frame-based video stream in the computer into AER and inject it at some point of the AER structure. This is necessary for test and debugging of complex AER systems. A set of software methods for converting digital frames into AER format are present in the literature. In this work we study the low level performance lacks of these methods monitoring internal performance hardware counters for an Intel Core 2 Quad. We discuss the results obtained and we propose improvements for those software methods that did not achieve real-time properties.