Bridging the Hardware-Software Divide in AI
The Data Exchange with Ben Lorica
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Optimizing Data Representation and Networking in AI
This chapter explores innovative methods in data representation, highlighting parallel logarithmic algorithms and the optimization of floating-point numbers. It also addresses networking challenges in large-scale training and emphasizes the need for software optimization to reduce communication overhead and enhance data locality.
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