Jialu Huang will present her preFPO on Monday April 9 at 1PM in Room 301 (note room!!) The members of her committee are: David August, advisor; David Walker and Kai Li, readers; Doug Clark and JP Singh, nonreaders. Everyone is invited to attend her talk. Her abstract follows below. ========================================================================================= Abstract: Automatic parallelization is a promising approach to deliver scalable multi-threaded programs for multi-core architectures. Most existing techniques parallelize independent loops and insert global synchronizations at the end of each loop invocation. For programs with few loop invocations, these global synchronizations do not limit parallel execution performance. However, for programs with many loop invocations, those synchronizations can easily become the performance bottleneck since they frequently force all threads to wait, losing potential parallelization opportunities. Some automatic parallelization techniques apply static analyses to enable cross-invocation parallelization. Instead of waiting, threads can execute iterations from follow-up invocations if they do not cause any conflict. However, static analyses must be conservative, and therefore cannot handle programs with irregular dependence patterns. In order to enable more parallelization across loop invocations, this thesis presents two novel automatic parallelization techniques: BLISS and SBS. Unlike existing techniques relying on static analyses, these two techniques take advantage of runtime information to achieve much more aggressive parallelization. BLISS constructs a custom runtime engine which non-speculatively observes dependences at runtime and synchronizes iterations only when necessary; while SBS applies software speculative barriers to permit some of the threads to execute past the invocation boundaries. The two techniques are complimentary in the sense that they can parallelize programs with potentially very different characteristics. SBS is most effective when a program's cross-invocation dependences rarely cause a runtime conflict. BLISS' runtime engine imposes a marginal amount of overhead, but it also enables the technique to effectively parallelize programs whose dependences can cause frequent conflicts. Preliminary implementation and evaluation demonstrate that both techniques can achieve much better scalability compared to existing automatic parallelization techniques. ==============================================================================================