Linley Fall 2018 Processor conference took place on Halloween. There was nothing too scary happening unless you are afraid of performance requirements for moving information or needing to run faster than ever for markets like automotive, industrial internet of things (IIoT) and data centers (cloud). Day one was full of interesting views, but it comes back to the ability to move data around and the requirement for memory to support the processing to turn data into information, thus accelerating intelligence.
Linley Gwennap kicked off the morning, using artificial intelligence (AI) as the example for architectures that will need to change to deliver performance for the future of neural networks being created. He outlined how the coming machine learning and deep learning workloads will stress traditional processing architectures.
Linley introduced the market examples of what NVIDIA is doing in automotive with Xavier, how IIoT will become adopted in consumer, (driving volume & adoption up) and how data centers are pushing the interface to PAM4 at 400G aided by the broader adoption of smart network interface controller (NIC) cards to offset the expense of costly processing to accommodate.