Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.
A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers at Arizona State University. Abstract “Neural networks have become a ...
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