Generalized Adaptive Variable Bit Truncation Method for Approximate Stochastic Computing
Stochastic computing as a computing paradigm is currently undergoing revival as the advancements in technology make it applicable especially in the wake of the need for efficient reduced precision computing for emerging applications. Recent research in stochastic computing exploits the benefits of approximate computing, called Approximate Stochastic Computing (ASC), which further reduces the operational overhead in implementing stochastic circuits. A new generalized adaptive method improving on ASC is proposed in this work. The proposed method has been discussed with two possible implementation variants - Area efficient and Time efficient. The proposed method has also been implemented in Matlab to compare against ASC and is shown to perform better than previous approaches for error-tolerant applications.
K. Pamidimukkala et al., "Generalized Adaptive Variable Bit Truncation Method for Approximate Stochastic Computing," Proceedings of the 2018 International SoC Design Conference (2018, Daegu, South Korea), pp. 218-219, Institute of Electrical and Electronics Engineers (IEEE), Nov 2018.
The definitive version is available at https://doi.org/10.1109/ISOCC.2018.8649979
2018 International SoC Design Conference, ISOCC 2018 (2018: Nov. 12-15, Daegu, South Korea)
Electrical and Computer Engineering
Keywords and Phrases
MATLAB; Adaptive methods; Bit-truncation method; Computing paradigm; Emerging applications; Recent researches; Reduced precision; Stochastic circuits; Stochastic computing; Stochastic systems
International Standard Book Number (ISBN)
International Standard Serial Number (ISSN)
Article - Conference proceedings
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01 Nov 2018