Machine learning is the latest technology transforming the world. Algorithms that used to work with the cloud are now scaling beyond to the edge. Applications include surveillance, ADAS, robotics and data centers. Developers are looking for ways to deploy complex systems quickly and easily.
For machine learning on the edge network, the optimal tradeoff among latency, power, cost, flexibility, scalability and time-to-market is provided by Xilinx. Its Software Defined System-on-Chip or SDSoC allows seamless integration of hardware and software, automating memory allocation, cache management, DMA and device interaction. The SDx development environment provides a common infrastructure for project creation, emulation, implementation and debug, allowing different embedded systems to be implemented easily.
The result is faster design, quick resolution of performance bottlenecks, optimum block-level connectivity, estimation in minutes and automated performance measurement. Xilinx also offers powerful tools like deep learning, accelerated software libraries and sensor boards and kits to facilitate the production of machine learning video systems.
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