A PulseWidth-IN-PulseWidth-Out Universal Nonlinear Processing Element for Time-Domain In-Memory Computing Systems

Time-Domain In-Memory Computing (TD-IMC) has emerged as a promising analog computing architecture for edge AI applications. However, the lack of developed hardware operators, especially general nonlinear operators, necessitates frequent cross-domain data transmission in practical TD-IMC systems, significantly reducing energy efficiency. In this work, we propose a PulseWidth-IN-PulseWidth-OUT Universal Nonlinear Processing Element (PIPO-UNPE) to address the challenges of nonlinear processing in analog computing. By implementing an RRAM-based two-layer ReLU network, the PIPO-UNPE performs universal nonlinear operations entirely in the time domain. Algorithmically, we introduce Dynamic Loss-Responsive Subset Enhancement (DLRSE) to boost the performance of this low-cost network in function approximation tasks. From a hardware perspective, we design an RRAM-based pulse-driven programmable current source and a low-latency dispersion comparator-based voltage-to-time converter (VTC) to enhance both the energy efficiency and precision of the PIPO-UNPE. Hybrid simulations reveal that the PIPO-UNPE consumes 912 uW of power while delivering a throughput of $\mathbf{1 0 M}$ NOPS (Nonlinear Operations Per Second). Incorporating the PIPO-UNPE into the TD-IMC accelerator can increase energy efficiency by a factor of 9.5 to 25, keeping the accuracy loss below 0.1%.