Workload-Specific Hardware Accelerators
Workload-specific hardware accelerators are becoming essential in large data centers for two reasons. One is that general-purpose processing elements cannot keep up with the workload demands or latency requirements. The second is that they need to be extremely efficient due to limited electricity from the grid and the high cost of cooling these devices. Sharad Chole, chief scientist and co-founder of Expedera, talks with Semiconductor Engineering about the role of neural processing units inside AI data centers, tradeoffs between performance and accuracy, and new challenges with chiplet-based multi-die assemblies.
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