NVLink is similar to a higher-bandwidth PCIe connection, except that multiple GPUs can be connected with it. It's primarily useful for very large convnets, whic

NVLink is similar to a higher-bandwidth PCIe connection, except that multiple GPUs can be connected with it. It's primarily useful for very large convnets, which use a lot of memory and can be bandwidth-limited. It doesn't require any particular modifications to a model or framework to take advantage of it. CAPI is much more flexible and interesting. It allows a CAPI-capable connected device access to a process's virtual memory. Essentially, you can extend the CPU's capabilities with CAPI. Usually this would be an FPGA (and the utility of FPGAs for machine learning is very much a research topic), but I could easily see a DSP being useful for voice recognition. GPUs can take advantage of it too, but ML work is usually just offloaded entirely to the GPU. CAPI is very very cool and designed by some very smart people. I'm excited what people will do with CAPI and FPGAs.