Alexandru Tanase

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We introduce a novel class of massively parallel processor architectures called invasive Tightly-Coupled Processor Arrays (TCPAs). The presented processor class is a highly parameterizable template which can be tailored before runtime to fulfill costumers' requirements such as performance, area cost, and energy efficiency. These programmable accelerators(More)
Nowadays, computer vision algorithms have countless application domains. On the one hand, these algorithms are typically computationally demanding, on the other hand, they are often used in embedded systems, which have stringent constraints on, e. g., size or power. In this work, we present the benefits of mapping compute-intensive imaging algorithms on(More)
In this work, we provide an overview of out high-level synthesis framework PARO. PARO is targeted at data flow dominant algorithms where most of the computational load lies in loop nests, defined by affine expressions. In Zn these loop definitions can be interpreted as half-spaces, which intersect to form convex polyhedra around the sets of loop iterations.(More)
High-Level Synthesis (HLS) has become a very popular instrument to facilitate rapid development of productionready implementations for FPGAs. Ever increasing flexibility of the frameworks, however, demands a very high level of domainspecific knowledge from the designer. Examples for such knowledge in window-based image processing are median computation and(More)
Optical flow is widely used in many applications of portable mobile devices and automotive embedded systems for the determination of motion of objects in a visual scene. Also in robotics, it is used for motion detection, object segmentation, time-to-contact information, focus of expansion calculations, robot navigation, and automatic parking for vehicles.(More)