Analysis and realization of Relaxed Consistency Memory model for multi-core CPU or GPU

Parallel and distributed systems that support the shared memory paradigm are becoming widely accepted in many areas of computing. The memory consistency model of a shared-memory multiprocessor system influences both the performance and the programmability of the system. Under optimal condition it is found that multithreading contributes to more than 50 percent of performance improvement, while the improvement from Relaxed Consistency Memory (RCM) models varies between 30-40 percent of total performance gain. The relaxed consistency memory model has been realized on a Graphics Processing Unit (GPU) using Open Computing Language (OpenCL) as the programming language. This memory model has been applied on a case study of high order matrix multiplication and their performance has been analysed in terms of two metrics: GPU Computation Percentage (GCP) and GPU Load Balance (GLB). With sufficient parallelism and high PCIe data transfer bandwidth, the RCM model on GPU gives the better performance in comparison to a sequential model on CPU.