Near fine grain parallel processing using static scheduling on single chip multiprocessors

With the increase of the number of transistors integrated on a chip, efficient use of transistors and scalable improvement of effective performance of a processor are getting im-portant problems. However, it has been thought that popular superscalar and VLIW would have difficulty to obtain scalable improvement of effective performance in future because of the limitation of instruction level parallelism. To cope with this problem, a single chip multiprocessor (SCM) approach with multi grain parallel processing inside a chip, which hierarchically exploits loop parallelism and coarse grain parallelism among subroutines, loops and basic blocks in addition to instruction level parallelism, is thought one of the most promising approaches. This paper evaluates effectiveness of the single chip multiprocessor architectures with a shared cache, global registers, distributed shared memory and/or local memory for near fine grain parallel processing as the first step of research on SCM architecture to support multi grain parallel processing. The evaluation shows OSCAR (Optimally Scheduled Advanced Multiprocessor) architecture having distributed shared memory and local memory in addition to centralized shared memory and attachment of global register gives us significant speed up such as 13.8% to 143.8% for four pro-cessors compared with shared cache architecture for applications which have been difficult to extract parallelism effectively.