Cluster Assignment of Global Values for Clustered VLIW Processors

摘要

In this paper high-level language (HLL) variables that are alive in a whole HLL function, across multiple scheduling units, are termed as global values. Due to their long live ranges and, hence, large impact on the schedule, the global values require different compiler optimizations than local values, which span across only one scheduling unit. The instruction scheduler for a clustered ILP processor, which is responsible for cluster assignment of operations and variables, faces a difficult problem of assigning global values to clusters. Our study shows that trivial assignments (e.g. mapping all global values into one cluster) may result in a severe cycle count overhead relative to the unicluster of up to 26.3% for a four cluster VLIW machine. This paper presents three advanced algorithms for assigning global values to clusters based on multi-pass scheduling and affinity of variables. Furthermore, we measure performance of these algorithms on optimized multimedia C applications and assess quality of our algorithms by comparing them to a practical higher performance bound derived from a vast random search. Our algorithms reduce the execution time overhead of the best simple algorithm round-robin from 10.5% to 5.9% for the two cluster VLIW machine and from 17.3% to 14.12% for the four cluster VLIW machine.