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There are two fundamentally different and complementary ways of accelerating machine learning workloads: By vertical scaling or scaling-up, where one adds more resources to a single machine Or 2. By horizontal scaling or scaling-out, where one adds more nodes to the system But when it comes to the degree of distribution within a machine learning…
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