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- W4378801078 abstract "Viterbi decoders are widely used in communication systems, natural language processing (NLP), and other domains. While Viterbi decoders are compute-intensive and power-hungry, we can exploit approximations for early design space exploration (DSE) of trade-offs between accuracy, power, and area. We present Locate, a DSE framework that uses approximate adders in the critically compute and power-intensive Add-Compare-Select Unit (ACSU) of the Viterbi decoder. We demonstrate the utility of Locate for early DSE of accuracy-power-area trade-offs for two applications: communication systems and NLP, showing a range of pareto-optimal design configurations. For instance, in the communication system, using an approximate adder, we observe savings of 21.5% area and 31.02% power with only 0.142% loss in accuracy averaged across three modulation schemes. Similarly, for a Parts-of-Speech Tagger in an NLP setting, out of 15 approximate adders, 7 report 100% accuracy while saving 22.75% area and 28.79% power on average when compared to using a Carry-Lookahead Adder in the ACSU. These results show that Locate can be used synergistically with other optimization techniques to improve the end-to-end efficiency of Viterbi decoders for various application domains." @default.
- W4378801078 created "2023-06-01" @default.
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- W4378801078 date "2023-06-05" @default.
- W4378801078 modified "2023-09-23" @default.
- W4378801078 title "Locate: Low-Power Viterbi Decoder Exploration using Approximate Adders" @default.
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- W4378801078 doi "https://doi.org/10.1145/3583781.3590314" @default.
- W4378801078 hasPublicationYear "2023" @default.
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