The monolithic 3D stacking (M3D) reduces the critical path delay, leveraging 1) short latency of a monolithic inter-tier via (MIV) and 2) short 2D interconnect and cell delay through smaller footprint. In this paper, we propose M3D stacked multiply-accumulate (MAC) units; MAC units have a relatively large number of long wires. With the Samsung 28 nm ASIC library, the M3D stacked MAC units reduce the critical path delay by up to 28.9%, compared to the conventional 2D structure. In addition, the M3D stacked MAC units reduce dynamic energy and leakage power by up to 9.6% and 21.7%, respectively. Compared to the TSV stacked MAC units, the M3D stacked MAC units consume less dynamic energy and leakage power by up to 37.1% and 73.6%, respectively. Though the 3D stacking technology inevitably causes higher peak temperature than the 2D structure, our thermal results show that the peak temperature of the M3D stacking is always lower than that of the TSV-based 3D stacking. Furthermore, when the size of the MAC unit is optimized in convolutional neural network (CNN) applications, the peak temperature of the M3D stacking is 88.3 °C at most, which is still under the threshold temperature.

单片3D堆叠（M3D）通过利用1）单片层间过孔（MIV）的短等待时间和2）较短的2D互连以及较小的占用空间来降低关键路径延迟。在本文中，我们提出了M3D堆叠乘累加（MAC）单元。MAC单元具有相对大量的长导线。与传统的2D结构相比，借助Samsung 28 nm ASIC库，M3D堆叠的MAC单元可将关键路径延迟降低多达28.9％。此外，M3D堆叠式MAC单元分别将动态能量和泄漏功率分别降低了9.6％和21.7％。与TSV堆叠式MAC单元相比，M3D堆叠式MAC单元消耗的动态能量和泄漏功率更少，分别高达37.1％和73.6％。尽管3D堆叠技术不可避免地会导致峰值温度高于2D结构，我们的热结果表明，M3D堆栈的峰值温度始终低于基于TSV的3D堆栈的峰值温度。此外，当在卷积神经网络（CNN）应用中优化MAC单元的大小时，M3D堆栈的峰值温度最高为88.3°C，仍然低于阈值温度。