Runtime Memory Controller Profiling with Performance Analysis for DRAM Memory Controllers

Abstract

The main memory system has become crucial not only because it has to meet an increasing bandwidth requirement, but also because it has to seamlessly support many concurrently executing applications. In order to improve memory performance, a memory controller with efficient arbitration is necessary. It is well known that memory performance is dependent on the memory access patterns. The offline performance analysis has difficulty analyzing the Dynamic Random Access Memory (DRAM) performance accurately because a huge set of trace patterns is needed. This paper proposes a novel profiler that is synthesized with a memory controller in order to monitor and analyze the memory controller performance at runtime. In this paper, five key metrics for performance evaluation are defined and they are monitored and evaluated at runtime by the proposed profiler. A prototype system with a processor core, a memory controller, DRAM modules, and peripheral devices are implemented on a field-programmable gate array (FPGA) board to carry out the experiments. It has been observed that the worst latency overhead differs for each benchmark. In addition, a new overall overhead estimation method is proposed to estimate the memory access latency overhead in time, and this method can be used to evaluate the performance of a certain memory arbitration method depending on running applications.