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Open Access Research on highly parallel embedded control system design and implementation method

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The pace of technology's advancements is ever-increasing and intelligent systems, such as those found in robots and vehicles, have become larger and more complex. These intelligent systems have a heterogeneous structure, comprising a mixture of modules such as artificial intelligence (AI) and powertrain control modules that facilitate large-scale numerical calculation and real-time periodic processing functions. Information technology expert Professor Masato Edahiro, from the Graduate School of Informatics at the Nagoya University in Japan, explains that concurrent advances in semiconductor research have led to the miniaturisation of semiconductors, allowing a greater number of processors to be mounted on a single chip, increasing potential processing power. 'In addition to general-purpose processors such as CPUs, a mixture of multiple types of accelerators such as GPGPU and FPGA has evolved, producing a more complex and heterogeneous computer architecture,' he says. Edahiro and his partners have been working on the eMBP, a model-based parallelizer (MBP) that offers a mapping system as an efficient way of automatically generating parallel code for multi- and many-core systems. This ensures that once the hardware description is written, eMBP can bridge the gap between software and hardware to ensure that not only is an efficient ecosystem achieved for hardware vendors, but the need for different software vendors to adapt code for their particular platforms is also eliminated.
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Keywords: AUTOMATIC MAPPING OF SYSTEMS; CODE GENERATION; COMBINATORIAL OPTIMISATION ALGORITHMS; MBP; MODEL BASED PARALLELIZER PROJECT; MODEL–BASED PARALLELIZER; MULTICORE; PARALLELIZATION; SHIM; SOFTWARE MODULES TO HARDWARE MODULES; eMBP

Document Type: Research Article

Publication date: December 1, 2019

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