By Lars Bauer, Jörg Henkel
Run-time model for Reconfigurable Embedded Processors via: Lars Bauer Jörg Henkel Embedded processors are the guts of embedded platforms. Reconfigurable embedded processors include a longer guide set that's applied utilizing a reconfigurable cloth (similar to a field-programmable gate array, FPGA). This booklet offers novel techniques, ideas, and implementations to extend the run-time adaptivity of reconfigurable embedded processors. techniques and strategies are offered in an available, but rigorous context. a posh, real looking H.264 video encoder software with a excessive call for for adaptivity is gifted and used for instance for motivation in the course of the publication. a unique, run-time method is tested to take advantage of the potential of adaptivity and specific approaches/algorithms are provided to enforce it. •Presents a brand new method of elevate the adaptivity of embedded processors; •Describes a unique method of expanding the adaptivity for reconfigurable processors, defined in a truly visual/imaginable demeanour, besides a really precise/formal demeanour; •Presents a fancy, practical H.264 video encoder program with a excessive call for for adaptivity and makes use of that instance for motivation/in-depth overview through the publication; •Describes a unique run-time approach that exploits the possibility of adaptivity and specific approaches/algorithms to enforce it.
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Extra info for Run-time Adaptation for Reconfigurable Embedded Processors
The CCA approach is based on coarse-grained reconfigurable elements and it supports a run-time placement of elementary data-flow graphs. This means, instead of preparing the configuration of the reconfigurable array at compile time (as done by ADRES), CCA identifies relevant computational kernels at compile time, but it creates configurations to accelerate them at run time. This allows that one application may be accelerated by different instantiations of the CCA reconfigurable array. To simplify the task of run-time placement, CCA is limited to a significantly narrowed hardware architecture.
Therefore, depending on the reconfiguration frequency,1 a highly parallel implementation might lead to a reduced performance in comparison to an SI implementation with limited parallelism, because the reconfiguration overhead problem diminishes the potential performance to some degree. For instance, if the software implementation of a computational block demands 10 ms execution time (ET) and a dedicated SI provides a 10× speedup for this computation but demands 4 ms reconfiguration overhead (RO) until the computation can start, then the resulting speedup is 10 ms ET/(4 ms RO + 1 ms ET) = 2×.
Are analyzed. 6 The process might be iterated several times until design constraints comply. A general overview of the benefits and challenges of ASIPs is given in [Hen03, KMN02]. Tool suites and architectural IPs for embedded customizable processors with different flavors are provided by major vendors like Tensilica [Tena], CoWare/ LisaTek [CoW], ASIP Solutions [ASI], ARC [ARC], and Target [Tar]. In addition, academic approaches like PEAS-III [IHT+00, KMTI03], LISA [HKN+01, ISS], and Expression [HGG+99] are available.