Self-scheduling, data synchronization and program transformation for multiprocessor systems

The limitation of vector supercomputing and of device speed has led to the development of multiprocessor supercomputers. Although large tightly-coupled shared-memory multiprocessor systems have become feasible, such systems cannot be considered successful, unless their numerous processors can coordinate with each other efficiently for a wide range of applications. Advanced software techniques and their supports from system architectures are keys to the success of modern multiprocessor supercomputers.; This dissertation first concentrates on two important software issues for large multiprocessor systems: processor scheduling and data synchronization.; Self-scheduling, an efficient dynamic heuristic scheduling, is a practical solution to the scheduling problem of multiprocessor systems. We propose several self-scheduling schemes which can be used by a compiler to generate self-scheduling object codes for parallel programs. Since busy-waiting is used to enforce cross-iteration data dependences, deadlocks in self-scheduling are possible. We identify the conditions that allow deadlock-free self-scheduling for different self-scheduling models and propose the use of an appropriate scheduling order for allocating processors to prevent deadlocks. Self-scheduling order also has significant impact on the performance of parallel loops with cross-iteration data dependences. We propose the shortest-delay self-scheduling (SDSS) order based on Doacross delays determined by cross-iteration data dependences. We show by simulation that SDSS can offer near-optimal performance in most cases. A compile-time program transformation for SDSS is also presented.; Data synchronization is necessary to enforce cross-iteration data data dependences. We propose a set of data-level synchronization instructions to support data synchronization. Compiler algorithms for generating these data-level synchronization instructions for different types of subscript functions are presented.; The last part of the dissertation addresses an architecture issue of large multiprocessor systems: "hot-spot" contention. We suggest the use of software combining to distribute "hot-spot" addressings. A number of software combining algorithms for different access patterns, such as barrier synchronization, fetch-and-add type of operations and semaphore P/V operations, are presented.