Yasoda Krishna Reddy Annapureddy,
V. Krishna Reddy,
- Student, Department of Computer Science engineering, Koneru Lakshmaiah education Foundation, Vaddeswaram, Andhra Pradesh, India
- Professor & Principal, Department of Computer Science Engineering, Koneru Lakshmaiah education Foundation, Vaddeswaram, Andhra Pradesh, India
Abstract
In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for their superior speed and lower latency compared to traditional storage solutions, are redefining the landscape of data-intensive tasks. Through the analysis of five pivotal research papers, this survey encapsulates the evolving dynamics of NVMe SSDs in enhancing performance, addressing challenges and laying the foundation for next breakthroughs in storage technology. The key findings highlight NVMe SSDs’ significant impact on improving throughput, reducing latency, and optimizing resource utilization in various settings. Additionally, the survey identifies existing bottlenecks and provides insights into potential areas of advancement. This survey underscores the essentialness of NVMe SSDs in contemporary and future computing infrastructures, indicating their importance for faster, more efficient data processing and storage solutions.
Keywords: NVMe SSDs, data-intensive computing, high performance computing (HPC), cloud storage optimization, big data processing
[This article belongs to Recent Trends in Parallel Computing ]
Yasoda Krishna Reddy Annapureddy, V. Krishna Reddy. Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs. Recent Trends in Parallel Computing. 2025; 12(03):01-21.
Yasoda Krishna Reddy Annapureddy, V. Krishna Reddy. Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs. Recent Trends in Parallel Computing. 2025; 12(03):01-21. Available from: https://journals.stmjournals.com/rtpc/article=2025/view=232636
References
- Yang Z, Hoseinzadeh M, Wong P, Artoux J, Mayers C, Evans DT, Bolt RT, Bhimani J, Mi N, Swanson S. H-NVMe: A hybrid framework of NVMe-based storage system in cloud computing environment. In 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC). 2017 Dec 10; 1–8.
- Gugnani S, Li T, Lu X. Nvme-cr: A scalable ephemeral storage runtime for checkpoint/restart with nvme-over-fabrics. In 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS). 2021 May 17; 172–181.
- Bhimani J, Yang J, Yang Z, Mi N, Xu Q, Awasthi M, Pandurangan R, Balakrishnan V. Understanding performance of I/O intensive containerized applications for NVMe SSDs. In 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC). 2016 Dec 9; 1–8.
- Bayati M, Bhimani J, Lee R, Mi N. Exploring benefits of nvme ssds for bigdata processing in enterprise data centers. In 2019 IEEE 5th International Conference on Big Data Computing and Communications (BIGCOM). 2019 Aug 9; 98–106.
- Boboila S, Desnoyers P. Performance models of flash-based solid-state drives for real workloads. In 2011 IEEE 27th Symposium on Mass Storage Systems and Technologies (MSST). 2011 May 23; 1–6.
- Kim B, Kim J, Noh SH. Managing array of {SSDs} when the storage device is no longer the performance bottleneck. In 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 17). 2017.
- Guz Z, Li H, Shayesteh A, Balakrishnan V. NVMe-over-fabrics performance characterization and the path to low-overhead flash disaggregation. In Proceedings of the 10th ACM International Systems and Storage Conference. 2017 May 22; 1–9.
- Kim HJ, Lee YS, Kim JS. {NVMeDirect}: A User-space {I/O} Framework for Application-specific Optimization on {NVMe}{SSDs}. In 8th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 16). 2016.
- Jung M, Choi W, Shalf J, Kandemir MT. Triple-A: A non-SSD based autonomic all-flash array for high performance storage systems. ACM SIGARCH Computer Architecture News. 2014 Feb 24; 42(1): 441–54.
- Mao B, Wu S, Duan L. Improving the SSD performance by exploiting request characteristics and internal parallelism. IEEE Trans Comput Aided Des Integr Circuits Syst. 2017;37(2):472-84.

Recent Trends in Parallel Computing
| Volume | 12 |
| Issue | 03 |
| Received | 06/06/2025 |
| Accepted | 23/06/2025 |
| Published | 30/10/2025 |
| Publication Time | 146 Days |
Login
PlumX Metrics