Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten ...

There are an increasing number of ways to do machine learning inference in the datacenter, but one of the increasingly popular means of running inference workloads is the combination of traditional ...

Over the past several years, the lion’s share of artificial intelligence (AI) investment has poured into training infrastructure—massive clusters designed to crunch through oceans of data, where speed ...

AMD (AMD) is rated a 'Buy' based on its architectural strengths and plausible 3-5 year EPS growth framework. AMD’s higher memory bandwidth and capacity position it well for the rapidly compounding ...

The vast proliferation and adoption of AI over the past decade has started to drive a shift in AI compute demand from training to inference. There is an increased push to put to use the large number ...

Machine-learning inference started out as a data-center activity, but tremendous effort is being put into inference at the edge. At this point, the “edge” is not a well-defined concept, and future ...