The design and implementation of compression techniques for profile guided compilation

Abstract

Advances in program profiling techniques have led to advances in compiler optimization techniques, and vice versa. This dissertation makes contributions in the areas of program profiling as well as profile-guided optimizations. More specifically, it designs and evaluates a new compressed representation for profile data such that profile guided optimizations can benefit from it. A type-based value profiling technique is also developed such that new data compression techniques can be designed to exploit value redundancy present in program data. A timestamped whole program path (TWPP+) representation is proposed to compress program traces which contain both control flow and memory address information. Instead of considering a trace as a stream of symbols, TWPP+ divides a complete trace into a control flow trace part and a memory dependence trace part; each part is then reorganized to allow fast retrieval of information during data flow analyses. Execution profiles can thus be integrated to help a broad range of compiler analyses and optimizations. Three different applications are shown to demonstrate the strength of this new representation. A type-based value profiling framework is developed to help identify redundancy in data values and thus design new data compression techniques for improving memory behavior. Two types of redundancies are identified in representations of small values and pointer addresses respectively. Both software and hardware approaches are proposed and evaluated to exploit these opportunities. The software approach through data compression transformations greatly reduces the memory footprint and speeds up the program executions with the help of six specially designed data compression instructions. The hardware approach employs compression to enable partial cache line prefetching resulting in consistent improvements in the program's execution time and reduction in memory traffic.