An Effective Heuristic for Simple Offset Assignment with Variable Coalescing

Abstract

Abstract. In many Digital Signal Processors (DSPs) with limited memory, programs are loaded in the ROM and thus it is very important to optimize the size of the code to reduce the memory requirement. Many DSP processors include address generation units (AGUs) that can perform address arithmetic (auto-increment and auto-decrement) in parallel to instruction execution, and without the need for extra instructions. Much research has been conducted to optimize the layout of the variables in memory to get the most benefit from auto-increment and autodecrement. The simple offset assignment (SOA) problem concerns the layout of variables for machines with one address register and the general offset assignment (GOA) deals with multiple address registers. Both these problems assume that each variable needs to be allocated for the entire duration of a program. Both SOA and GOA are NP-complete. In this paper, we present a heuristic for SOA that considers coalescing two or more non-interfering variables into the same memory location. SOA with variable coalescing is intended to decrease the cost of address arithmetic instructions as well as to decrease the memory requirement for variables by maximizing the number of variables mapped to the same memory slot. Results on several benchmarks show the significant improvement of our solution compared to other heuristics. In addition, we have adapted simulated annealing to further improve the solution from our heuristic.

A new heuristic for SOA problem based on effective tie break function

“…This problem is formulated as Coalesced SOA (CSOA). Recent work in this direction is that of Salamy and Ramanujam [12]. As mentioned, this work depends on the feature of variable coalescing which is not the case in this paper.…”

Solving the simple offset assignment problem as a traveling salesman

“…The approach to group such variables is called variable coalescing. Ottoni et al [23] presented a first heuristic which was followed by another one by Salamy and Ramanujam [26]. Recently, the latter authors also developed an ILP formulation for offset assignment with variable coalescing [27].…”

Storage optimization through code size reduction for digital signal processors

“…So instead of always selecting an edge as in OA, COA can either select an edge or coalesce two variables that meet the three conditions listed above. Some works [15], [22], [17] established the importance of variable coalescing to decrease the number of update instructions as well as to decrease the variables' stack size. Consider the simple example in Figure 1 assuming only one available AR.…”