Baking Specialization into Hardware Cools CPU Concerns

September 21, 2016 Nicole Hemsoth As Moore’s Law spirals downward, ultra-high bandwidth memory matched with custom accelerators for specialized workloads might be the only saving grace for the pace of innovation we are accustomed to. With advancements on both the memory and ASIC sides driven by machine learning and other workloads pushing greater innovation, this could be great news for big datacenters with inefficient legions of machines dedicated to ordinary processing tasks—jobs that could far more efficient with more tailored approaches. We have described this trend in the context of architectures built on stacked memory with FPGAs and other custom accelerators inside recently, and we expect to see more workloads targeted for specialized accelerator or processors. The problem with that approach is expense, or ROI. Designing and fabbing a custom…


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