A Memory Access Performance Detection and Optimization Driven by Address Mapping

In the development process of multi-core processors, the Network on Chip optimizes the storage structure, but the problem of “storage wall” still exists. There are many ways to alleviate this problem. The improvement of memory access performance can be obtained for appropriate address mapping between cache levels. As far as the performance index of address mapping is concerned, it can be considered from the perspectives of memory access bandwidth and latency in different levels of the storage system. Therefore, a module-level detection tool is designed to test the memory access performance. Based on the hardware emulation acceleration platform, this tool solves the online/offline data collection of memory access bandwidth and latency. And it implements the functions for extremely long simulation times, which is data capture, analysis, and processing. Under different address mapping and data types of different application scenarios, This tool tests memory access performance between cache modules. Based on the data-affinity address cross-mapping method, this thesis proposes an address mapping optimization scheme that binds the directory controller unit and the local memory. Through the module-level memory access performance test, the optimized data affinity and low-order address cross-mapping method increases the memory access bandwidth by 8% and the maximum bandwidth by 9% when processing scheduling-intensive data. In a word, this thesis establishes the memory access performance analysis method which is “benchmark test program, module-level memory access performance detection, address mapping optimization and configuration”.