A GSA-Based Compiler Infrastructure to Extract Parallelism from Complex Loops

This paper presents a new approach for the detection of coarse-grain parallelism in loop nests that contain complex computations, including subscripted subscripts as well as conditional statements that introduce complex control flows at run-time. The approach is based on the recognition of the computational kernels calculated in a loop without considering the semantics of the code. The detection is carried out on top of the Gated Single Assignment (GSA) program representation at two different levels. First, the use-def chains between the statements that compose the strongly connected components (SCCs) of the GSA use-def chain graph are analyzed (intra-SCC analysis). As a result, the kernel computed in each SCC is recognized. Second, the use-def chains between statements of different SCCs are examined (inter-SCC analysis). This second abstraction level enables the detection of more complex computational kernels by the compiler. A prototype was implemented using the infrastructure provided by the Polaris compiler. Experimental results that show the effectiveness of our approach for the detection of coarse-grain parallelism in a suite of real codes are presented