Pouya Esmaili-Dokht

Pouya Esmaili-Dokht, Arash Yadegari, Victor Xirau et al.

Memory simulators are used to estimate application performance on advanced memory systems, yet they may exhibit significant discrepancies compared to real hardware. This paper investigates two key questions: (1) what causes these inaccuracies, and (2) how can simulators be properly validated to ensure reliable performance predictions. We propose a methodology that evaluates memory performance from three complementary perspectives: the memory simulator, the CPU-memory interface, and the application. Our analysis reveals that these perspectives can diverge substantially, with application-level performance often decoupled from internal simulator statistics. We identify the CPU-memory interface as the primary source of these inaccuracies. To address these problems, we implement a set of corrections and enhancements that improve the fidelity of integrated simulators. We evaluate these changes across multiple widely used simulators, including Ramulator, Ramulator 2, and DRAMsim3 integrated with ZSim. The results show that correcting interface-related issues is essential to achieve simulation outcomes that closely resemble actual system performance.

Pau Díaz, Mariana Carmin, Pouya Esmaili-Dokht et al.

Multiplexed Rank DIMMs (MRDIMMs) have recently emerged as memory devices that enable higher bandwidth without increasing DRAM chip frequencies. This paper presents a detailed performance, power and energy evaluation of a production server with high-end MRDIMM main memory. The memory system upgrade from conventional registered DIMMs (RDIMMs) to MRDIMMs extends the bandwidth by 41% yielding 27-41% higher performance for bandwidth-bound workloads. Additionally, the latency improvement reaches hundreds of nanoseconds, benefiting a broad class of workloads sensitive to memory latency. At the same bandwidth utilization levels, RDIMMs and MRDIMMs exhibit similar power consumption. In the MRDIMM-extended bandwidth region, the performance improvements largely exceed the power increase, delivering up to 30% server energy savings for memory-bound workloads.