Heterogeneous Computing Is About Optimizing Resources

By Gary Hilson, EETimes (November 8, 2021)

The rapid emergence of the Compute Express Link (CXL) specification is an excellent example of heterogenous computing — but not all heterogenous computing is necessarily CXL. Rather, it’s about connecting to whatever mix of compute, memory, and storage will best tackle a given workload, without out the need to over-provision.

While the new protocol has as quickly gained traction to provide more efficient access to resources including memory, CXL is part of a broader trend in computing overall as data becomes less centralized and gets pushed into the edge to be used in more diverse workloads and a wider variety of devices.

It may sound flashy, said Ryan Baxter, senior director of Micron Technology’s cloud, computing and networking business unit, but heterogenous ultimately means it’s not monolithic and no longer just a standard memory connected to an x86 CPU. “You can take that tool to battle, but it may not be the most efficient anymore.” While it’s possible to do machine learning training using x86 servers, he said, “it’s not an architecture well-suited to be able to tackle that kind of problem.”

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