Parallel Unary Computing Based on Function Derivatives

ACM Transactions on Reconfigurable Technology and Systems(2020)

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摘要
AbstractThe binary number representation has dominated digital logic for decades due to its compact storage requirements. An alternative representation is the unary number system: We use N bits, from which the first M are 1 and the rest are 0 to represent the value M/N. One-hot representation is a variation of the unary number system where it has one 1 in the N bits, where the 1’s position represents its value. We present a novel method that first converts binary numbers to unary using thermometer (one-hot) encoders and then uses a “scaling network” followed by voting gates that we call “alternator logic,” followed by a decoder to convert the numbers back to the binary format. For monotonically increasing functions, the scaling network is all we need, which essentially uses only the routing resources and flip-flops on a typical FPGA architecture. Our method is clearly superior to the conventional binary implementation: Our area×delay cost is on average only 0.4%, 4%, and 39% of the binary method for 8-, 10-, and 12-bit resolutions, respectively, in thermometer encoding scheme, and 0.5%, 15%, and 147% in the one-hot encoding scheme. In terms of power efficiency, our one-hot method is between about 69× and 114× better compared to conventional binary.
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关键词
Unary computing, scaling network, alternator logic, stochastic computing, thermometer code
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