Resource-Constrained High-Level Datapath Optimization in ASIP Design

In this work, we study the problem of optimizing the datapath under resource constraint in the high-level synthesis of Application-Specific Instruction Processor (ASIP). We propose a two-level dynamic programming (DP) based heuristic algorithm. At the inner level of the proposed algorithm, the instructions are sorted in topological order, and then a DP algorithm is applied to optimize the topological order of the datapath. At the outer level, the space of the topological order of each instruction is explored to iteratively improve the solution. Compared with an optimal brutal-force algorithm, the proposed algorithm achieves near-optimal solution, with only 3 % more performance overhead on average but significant reduction in runtime. Compared with a greedy algorithm which replaces the DP inner level with a greedy heuristic approach, the proposed algorithm achieves 48 % reduction in performance overhead