Study on parallelizing compiters with a granularity tuning mechanism

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We aim to establish the fundamental technology of parallelizing compilers with a granularity tuning mechanism for efficient parallel processing. The parallelizing compiler generates a parallel object program, which will be executed in the shortest time on a parallel computer, by matching its hardware characteristics with parallel properties of a given application program. The main results are as follows :1. A new static parallelizing scheme is proposed, in which apart of a target sequential program is divided into parallel tasks with optimal granularity by using the LogP model as an abstract parallel machine. Do loops, do across loops and recursive function calls are applied for granularity tuning, and evaluation studies are carried out on some different parallel computers.An efficient execution mechanism for coarse-grain parallel processing is proposed for distributed memory parallel computers. The mechanism can be realized to transform a given sequential program into a coarse-grain task graph with execution start conditions as well as data reaching conditions as a function of parallelizing computers.3. A parallelizing compiler with a coarse-grain parallel processing function is experimentally constructed. The conventional Open MP compiler is utilized to translate the coarse-grain task graph with Open MP primitives into an executable parallel C program.4. A novel software distributed shared memory (SDSM) is proposed, which reduces memory consistency overhead by reflecting characteristics of application programs at a middleware level. The SDSM scheme is implemented in such parallel machine environment as a heterogeneous workstation cluster and an SMP-type personal computer cluster.