Cost-Effective Reconfigurable MCM with Common-Value Elimination and Alignment

Multiple constant multiplication (MCM) generates area/energy-efficient circuit with additions and shifts for FIR filters and DNN inference acceleration. Reconfigurable MCM (ReMCM) enables time-multiplexing execution of MCM circuits for multiple constant sets by reusing adders across different sets. Finding a shift-add-mux circuit in ReMCM, however, generally relies on a rigid order of constants, which may cause unnecessary topology conflicts and thereby incur a power/area overhead. To address the problem, this work proposes an Adaptive Grouping Compatible Graph Synthesis (AG-CGS) framework for ReMCM, which reorders constants to enhance power/area efficiency. Employing an (index, value) data structure for a constant, AG-CGS introduces two novel techniques in ReMCM: intra-set common value elimination (Intra-SCE) and inter-set common value alignment (Inter-SCA). Consequently, AG-CGS enables searching for a cost-effective circuit associated with reordered coefficients to reduce redundant computations. The experimental results demonstrate that AG-CGS reduces area by up to 58.1%, 16.3%, and 13.8%, and energy by up to 63.1%, 15.2%, and 12.1%, compared to [1], [2], and [3], respectively.