Optimization based on the minimum maximal k-partial-matching problem of finite states machines with input multiplexing

Abstract

Finite State Machines with Input Multiplexing (FSMIMs) were proposed in previous work as a technique for efficient mapping Finite State Machines (FSMs) into ROM memory. In this paper, we present new contributions to the optimization process involved in the implementation of FSMIMs in Field Programmable Gate Array (FPGA) devices. This process consists of two stages: (1) the simplification of the bank of input selectors of the FSMIM, and (2) the reduction of the depth of the ROM. This has a significant impact both on the number of used Look-Up Tables (LUTs) and on the number of the Embedded Memory Blocks (EMBs) required by the ROM. For the first stage, we present two approaches to optimize FSMIM implementations based on the Minimum Maximal k-Partial Matching (MMKPM) problem: one of them applies the greedy algorithm for the MMKPM problem, and the other based on a new multiobjetive variant of the MMKPM and its corresponding Integer Linear Programing formulation. We also propose a modification of the second stage, in which the characteristics of EMBs are taken into account to improve implementation results. The new optimization process significantly reduces the number of used FPGA resources with respect to the previous one. In addition, the proposed approaches achieve an adequate trade-off between the usage of EMBs and LUTs with respect to conventional FSM implementations based on ROM and to those based on LUT.