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Nonvolatile-memory-based computing in memory (nvCIM) [1–6] is ideal for low-power edge-Al devices requiring neural network (NN) parameter storage in the power-off mode, a rapid response to device wake-up, and high energy efficiency for MAC operations <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(EFMAC)</tex> . Current analog nvCIMs impose a tradeoff between the signal margin (SM) and the number of accumulations <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(NACU)</tex> per cycle versus <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC</tex> and computing latency <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(TCD-MAC)</tex> . Near-memory computing (NMC), with high precision for inputs (IN), weights (W), and outputs (OUT), and a high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NACU</tex> is a trend to improve <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC, TCD-MAC</tex> , and accuracy. A prior STT-MRAM NMC [1] uses vertical-weight mapping (VWM) to improve the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC</tex> ; however, further improvement is challenging: due to (1) the large energy consumption in reading repetitious weight data across multiple inputs for a single NN-layer; (2) a high bitstream toggling-rate (BTR) for digital MAC circuits <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(DCMAC)</tex> reduces <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC</tex> , and; (3) a limited SM and memory readout latency <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(TCD-M)</tex> for memories with a small R-ratio (e.g. STT-MRAM, see Fig. 33.2.1). In developing an STT-MRAM nvCIM macro, this work moves beyond circuit-level novelty by using system-software-circuit co-design. This work achieves a high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC</tex> , a short <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TCD-M</tex> , a high read bandwidth (R-BW), a high IN-W-OUT precision, and a high <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NACU</tex> by using the novel schemes: (1) a hardware based weight-feature aware read (WFAR) to reduce weight accesses and improve <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC</tex> with a minimal area overhead; (2) toggling-aware weight-tuning (TAWT) to obtain fine-tuned weights <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(WFT)</tex> with a low BTR, which is based on VWM to enhance the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC</tex> of the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DCMAC</tex> ; (3) a differential charge-accumulating margin-enhanced voltage-sensing amplifier (DCME-VSA) to enhance the SM, while reducing the T <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CD</inf> - <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</inf> . The proposed 22-nm S-Mb STT-MRAM NMC nvCIM macro achieves the highest R-BW <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(436GB/s)</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EFMAC(46.4-160.1TOPS/W)</tex> for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">NACU=576</tex> for SblN - SbW - 26bOUT.
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Chiu et al. (2023) studied this question.
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