Data Access and Storage Management for Embedded Programmable Processors
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Data Access and Storage Management for Embedded Programmable Processors
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Cortex-R52 Most advanced processor for functional safety. We have a dedicated site for Germany. Authors: Catthoor , F. Data Access and Storage Management for Embedded Programmable Processors gives an overview of the state-of-the-art in system-level data access and storage management for embedded programmable processors. The targeted application domain covers complex embedded real-time multi-media and communication applications. Many of these applications are data-dominated in the sense that their cost related aspects, namely power consumption and footprint are heavily influenced if not dominated by the data access and storage aspects.
The material is mainly based on research at IMEC in this area in the period In order to deal with the stringent timing requirements and the data dominated characteristics of this domain, we have adopted a target architecture style that is compatible with modern embedded processors, and we have developed a systematic step-wise methodology to make the exploration and optimization of such applications feasible in a source-to-source precompilation approach.
senjouin-renkai.com/wp-content/untraceable/whatsapp-sniffer-gratis-para-tablet.php Among other techniques, ASSPs deliver this efficiency through the use of specialized coprocessors and accelerators. And, because ASSPs are by definition focused on a specific application, they are usually provided with extensive associated software. This same specialization, however, means that an ASSP designed for vision is typically not suitable for other applications. ASSPs' unique architectures can also make programming them more difficult than with other kinds of processors; some ASSPs are not user-programmable.
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General-purpose CPUs While computer vision algorithms can run on most general-purpose CPUs, desktop processors may not meet the design constraints of some systems. Graphics Processing Units High-performance GPUs deliver massive amounts of parallel computing potential, and graphics processors can be used to accelerate the portions of the computer vision pipeline that perform parallel processing on pixel data.
Digital Signal Processors DSPs are very efficient for processing streaming data, since the bus and memory architecture are optimized to process high-speed data as it traverses the system. Vision-Specific Processors and Cores Application-specific standard products ASSPs are specialized, highly integrated chips tailored for specific applications or application sets.