Unleashing the Power of NVMe in Cloud: A Complete Software-Defined Emulation Study - Mahdi Siamaki; Bardia Safaei (IEEE Access)
Non-Volatile Memory Express (NVMe) is revolutionizing cloud storage by offering high throughput, low latency, and efficient resource utilization. Understanding its performance characteristics under diverse workload conditions is crucial for optimizing storage configurations in cloud environments. Accordingly, this study leverages NVMeVirt, a powerful software-defined NVMe emulator, to investigate the impact of various workload characteristics on critical performance metrics. We analyze the influence of I/O distribution patterns (sequential, random, and Zipfian), queue depths, and the number of concurrent jobs on throughput, latency, and IOPS. We also analyze the energy consumption of both NVMe and SATA SSDs. Results demonstrate that NVMeVirt effectively emulates NVMe SSDs, exhibiting high throughput and low latency across diverse workloads. Sequential workloads consistently achieve higher throughput and significantly lower latency compared to random and Zipfian workloads, particularly at higher queue depths. Specifically, NVMe achieves up to 8.72% higher throughput and 34.89% lower latency than SATA for sequential workloads. This highlights the importance of aligning storage configurations with applications’ anticipated data access patterns. Our analysis also reveals the potential for optimizing energy efficiency by carefully adjusting workload parameters and storage configurations. Random and Zipfian workloads, due to increased seek operations and internal SSD activity, demonstrate higher energy consumption, underscoring the need for efficient data management strategies in cloud environments. This study provides valuable insights into the performance characteristics of NVMe SSDs and their advantages over SATA SSDs under various workload conditions. It highlights the importance of considering data access patterns and storage configurations for optimizing performance and energy efficiency in cloud-like environments. The findings of this paper can provide researchers with an optimized design and deployment of NVMe-based storage systems in cloud data centers to meet the demands of modern data-intensive applications effectively.