A Low-Latency Memory Architecture using 3D XPoint and Memristor Technologies

Latency bottlenecks in modern memory hierarchies pose significant challenges for contemporary computing systems, particularly in domains such as AI and real-time processing. Traditional memory technologies like DRAM and SRAM are approaching their scalability limits. Emerging memory technologies, including Memristors and 3D XPoint, offer a promising avenue for reducing these bottlenecks. This paper presents a comprehensive architectural analysis of a memory hierarchy integrating these emerging technologies, evaluating latency, power efficiency, and cache performance through detailed simulation using gem5. We simulate multiple workloads to demonstrate how these technologies substantially improve memory performance, energy efficiency, and scalability. Our results show an average latency reduction of 37% and energy savings of up to 52% compared to traditional architectures, with some workloads experiencing improvements of up to 60% in both metrics. We demonstrate a 10°C reduction in peak temperature and 46% decrease in power density compared to traditional DRAM-based systems, while achieving a 2.3× improvement in Mean Time To Failure (MTTF). Furthermore, we provide an in-depth analysis of the scalability and potential limitations of the proposed architecture, offering insights into the future of memory hierarchies and their impact on overall system performance.