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Technology Stocks : Investing in Exponential Growth

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From: Paul H. Christiansen	2/18/2018 1:05:05 PM
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Inference is the Hammer That Breaks the Datacenter Two important changes to the datacenter are happening in the same year—one on the hardware side, another in software. And together, they create a force big enough to blow away the clouds, at least over the long haul. As we covered this year from a datacentric (and even supercomputing) point of view, 2018 is the time for Arm to shine. With a bevy of inroads to commercial markets at the high-end all the way down to the micro-device level, the architecture presents a genuine challenge to the processor establishment. And now, coupled with the biggest trend since cloud or big data (which ironically could be replaced in various ways by this contender) machine learning comes steamrolling along, changing the way we could think about the final product of training—inference. Deep learning training has a clear winner on the hardware side. There is little doubt the GPU reigns supreme here and it has in fact bolstered the various cloud providers to rush to the latest GPU offerings to serve up for both high performance computing and training needs. Google’s TPU and the other architectures have a role here too, but for the mainstream trainers (if there are enough of them yet to classify a middle ground) are Nvidia GPU-centric. The story for inference is not so clean and easy. This is for a few different reasons, including the big one—the compute needed for training is dramatically different than what inference requires. Ultra-low power, reduced precision are key characteristics and accordingly, a host of existing device types have been moved in to fill demand and get a new breath of life; from DSPs to FPGAs to very small custom ASICs that once only had very domain specific markets to fill—all of these (and little GPUs too) have a chance. *Read More* -The Next Platform

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