Feature: Programmable devices
ASSPs can deliver performance and
power efficiency but are fixed. When requirements change, new silicon is needed, incurring significant cost, effort and time. There will continue to be a need for general-purpose processors and ASSPs, but as technology evolution cycles continue to accelerate, it’s increasingly challenging for fixed- silicon devices to keep up.
Adaptive computing Built on FPGA technology, adaptive computing allows DSAs to be dynamically built in silicon. Adaptive computing therefore allows these architectures to be dynamically updated as requirements change, freeing developers from lengthy ASIC design cycles and exorbitant NRE costs. DSAs can be updated over the air (OTA), and not just the software, but the hardware too – especially important as processing becomes more distributed. For example, the 2011 Mars rover Curiosity and the recently- launched Perseverance both contain adaptive computing. Perseverance uses adaptive computing for its comprehensive vision processor. Built using an FPGA-based platform, it accelerates AI and non-AI visual tasks, including image rectification, filtering, detection and matching. Images sent by Perseverance to NASA are then processed using adaptive computing. If a new algorithm is invented
during the eight months it takes Perseverance to reach Mars, or a hardware bug is discovered, adaptive computing allows hardware updates to be sent remotely, over the air or, in this case, over space. These updates are done quickly and easily, as a software update. In remote deployments, remote hardware updates are more than just a convenience, they are a necessity. Adaptive computing can be
deployed from the cloud to the edge to the endpoint, bringing the latest architectural innovations to every part of end-to-end applications. This is possible thanks to a wide range of
www.electronicsworld.co.uk February 2021 27 Xilinx Versal ACAP chip
adaptive computing platforms – from large capacity devices on PCIe accelerator cards in data centres, to small, low-power devices suitable for the endpoint processing needed by IoT applications. Adaptive computing can be used
to build all manner of optimised DSAs, from latency-sensitive applications such as autonomous driving and real-time streaming video, to signal processing in 5G, and the data processing of unstructured databases. And, with today’s hardware abstraction tools, software and AI developers can now take full advantage without needing to be hardware experts.
Xilinx Versal Premium series of devices
It's a win-win So, why care about the benefits of adaptive computing? With billions of intelligent, interconnected devices constantly communicating with each other and data centres, the amount of data being generated, processed and consumed is staggering. Adaptive computing brings higher processing capability with lower cost and power consumption. This reduces costs for end consumers, and lowers electricity usage. It’s a true win-win situation. There will continue to be a need for
general-purpose processors in the future, but adaptive devices will be critical in supporting the increased processing demands of AI in next computing era.
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