Today’s AI and ML systems use proprietary interconnects, which limits the choices available to customers. CXL technology promises to enable greater interoperability, and this is the focus for Xconn Technology. In this episode of Utilizing CXL, Gerry Fan of Xconn joins Stephen Foskett and Craig Rodgers to discuss the ways that CXL can improve machine learning processing. The CXL Consortium is working with nearly every company in the IT industry to bring this promise to life, but we need hardware and software to enable memory pooling, device sharing, and more. The initial CXL products enable right-sizing memory, regardless of the specific architectural details of the CPU chosen. The next addition will be disaggregated and pooled memory using CXL switches, and this is coming to market in the next year or so. This will enable massive pools of memory on-demand for intensive applications. Xconn promises to make memory pooling available to CXL 1.1 hosts as well, and is working on a fabric manager to enable this.
- Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.
- Craig Rodgers, Solutions Architect at Camlin Group. Connect with Craig on LinkedIn and follow him on Twitter at CraigRodgersms.
- Gerry Fan, Cofounder CEO, Xconn Technology. Connect with Gerry on LinkedIn.
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