Carbon nanotube networks made with high purity and ultraclean interfaces can be used to make a tensor processing unit that contains 3,000 transistors in a systolic array architecture to improve energy efficiency in accelerating neural network tasks.
Carbon nanotube networks made with high purity and ultraclean interfaces can be used to make a tensor processing unit that contains 3,000 transistors in a systolic array architecture to improve energy efficiency in accelerating neural network tasks.
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