Compiler Optimization Techniques for OpenMP Programs

We have developed compiler optimization techniques for explicit parallel programs using the OpenMP API. To enable optimization across threads, we designed dataflow analysis techniques in which interactions between threads are effectively modeled. Structured description of parallelism and relaxed memory consistency in OpenMP make the analyses effective and efficient. We developed algorithms for reaching definitions analysis, memory synchronization analysis, and cross‐loop data dependence analysis for parallel loops. Our primary target is compiler‐directed software distributed shared memory systems in which aggressive compiler optimizations for software‐implemented coherence schemes are crucial to obtaining good performance. We also developed optimizations applicable to general OpenMP implementations, namely redundant barrier removal and privatization of dynamically allocated objects. Experimental results for the coherency optimization show that aggressive compiler optimizations are quite effective for a shared‐write intensive program because the coherence‐induced communication volume in such a program is much larger than that in shared‐read intensive programs.