Areanna claims 100 TOPS/W in simulation
By Rick Merritt, EETimes
July 22, 2019
SAN JOSE — In his spare time, an engineer at Tektronix sketched out a novel deep-learning accelerator, and now his two-person startup is the latest example of the groundswell of enthusiasm that deep learning is generating.
Behdad Youssefi defined an SRAM with specialized cells that can handle the matrix multiplication, quantization, storage and other jobs needed for an inference processor. After four years solo work on the concept originally planned as a PhD thesis, he formed startup Areanna with a colleague at Tektronix and a Berkeley professor as an advisor.
In Spice simulations the design delvers more than 100 tera-operations/second/watt when recognizing handwritten digits using 8-bit integer math. Youssefi claims it could beat Google’s TPU in computational density by an order of magnitude.
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