optimization opportunities created by global data reordering
Memory access has proven to be one of the bottlenecks in modern architectures. Improving memory locality and eliminating the amount of memory access can help release this bottleneck. We present a method for link-time profile-based optimization by reordering the global data of the program and modifying its code accordingly. The proposed optimization reorders the entire global data of the program, according to a representative execution rate of each instruction (or basic block) in the code. The data reordering is done in a way that enables the replacement of frequently-executed Load instructions, which reference the global data, with fast Add Immediate instructions. In addition, it tries to improve the global data locality and to reduce the total size of the global data area. The optimization was implemented into FDPR (Feedback Directed Program Restructuring), a post-link optimizer, which is part of the IBM AIX operating system for the IBM pSeries servers. Our results on SPECint2000 show a significant improvement of up to 11\% (average 3\%) in execution time, along with up to 97.9\% (average 83\%) reduction in memory references to the global variables via the global data access mechanism of the program.
optimality global data memorialized access proven architecture locality help method code instruction blocking data locality size feedback direct operating system server timing reduction variability profiles linking