ADVANCES IN PARALLEL COMPUTING ARCHITECTURES AND DISTRIBUTED FILE SYSTEMS: A COMPREHENSIVE ANALYSIS OF GPU, FPGA, AND MULTICORE SYSTEMS FOR EFFICIENT DATA MANAGEMENT
Abstract
The continuous evolution of computational paradigms has necessitated the exploration and optimization of parallel computing architectures and distributed file systems. This research presents an in-depth analysis of GPU, FPGA, and multicore processor architectures, emphasizing their applications in data-parallel problems and large-scale distributed environments. It examines the historical progression of parallel architectures, from early massively parallel processors to contemporary high-performance multicore and heterogeneous systems, highlighting the design principles that underpin performance scalability and efficiency. Furthermore, the study investigates distributed file systems, including the Google File System (GFS) and HDFS, with a particular focus on handling small file challenges and enhancing throughput for large-scale data processing. A systematic discussion of the architectural implications, interconnection networks, and memory hierarchies illustrates how hardware innovations influence software performance in parallel and distributed contexts. The research identifies critical gaps in current methods, such as small file optimization in distributed storage, heterogeneous processing resource utilization, and workload balancing across multi-node systems. By synthesizing theoretical and empirical insights, this paper provides a framework for future developments in high-performance computing and data management, proposing strategies for integrating GPU, FPGA, and multicore systems into distributed storage and processing frameworks. The findings emphasize the importance of architectural awareness in software design and the necessity of optimizing both hardware and software layers for achieving maximal computational efficiency and reliability in distributed systems.
Keywords
Parallel computing, GPU architecture
References
- Navarro, C.A.; Hitschfeld-Kahler, N.; Mateu, L. A survey on parallel computing and its applications in data-parallel problems using GPU architectures. Commun. Comput. Phys. 2014, 15, 285–329.
- Farooq, U.; Marrakchi, Z.; Mehrez, H. FPGA architectures: An overview. In Tree-Based Heterogeneous FPGA Architectures: Application Specific Exploration and Optimization; Springer: Midtown Manhattan, New York, USA, 2012; pp. 7–48.
- Halsted, D. The origins of the architectural metaphor in computing: Design and technology at IBM, 1957–1964. IEEE Ann. Hist. Comput. 2018, 40, 61–70.
- Chawan, M.P.; Patle, B.; Cholake, V.; Pardeshi, S. Parallel Computer Architectural Schemes. Int. J. Eng. Res. Technol. 2012, 1, 9.
- Batcher. Design of a massively parallel processor. IEEE Trans. Comput. 1980, 100, 836–840.
- Leiserson, C.E.; Abuhamdeh, Z.S.; Douglas, D.C.; Feynman, C.R.; Ganmukhi, M.N.; Hill, J.V.; Hillis, D.; Kuszmaul, B.C.; St. Pierre, M.A.; Wells, D.S.; et al. The network architecture of the Connection Machine CM-5. In Proceedings of the Fourth Annual ACM Symposium on Parallel Algorithms and Architectures, San Diego, CA, USA, 29 June–1 July 1992; pp. 272–285.
- Alverson, B.; Froese, E.; Kaplan, L.; Roweth, D. Cray XC Series Network; White Paper WP-Aries01-1112; Cray Inc.: Seattle, WA, USA, 2012.
- Sagar Kesarpu. Contract Testing with PACT: Ensuring Reliable API Interactions in Distributed Systems. The American Journal of Engineering and Technology, 7(06), 14–23, 2025. https://doi.org/10.37547/tajet/Volume07Issue06-03
- Keckler, S.W.; Hofstee, H.P.; Olukotun, K. Multicore Processors and Systems; Springer: Berlin/Heidelberg, Germany, 2009.
- McClanahan, C. History and evolution of gpu architecture. Surv. Pap. 2010, 9, 1–7.
- Kshemkalyani, A.D.; Singhal, M. Distributed Computing: Principles, Algorithms, and Systems; Cambridge University Press: Cambridge, UK, 2011.
- Ghemawat, S.; Gobioff, H.; Leung, S.T. The google file system. ACM SIGOPS Oper. Syst. Rev., 73, 29–43, 2003.
- Jiang, L.; Li, B.; Song, M. The optimization of HDFS based on small files. Proc. 2010 3rd IEEE Int. Conf. Broadband Network and Multimedia Technology (IC-BNMT), 912–915, 2010.
- Zhuo, S.; Wu, X.; Zhang, W.; Dou, W. Distributed file system and classification for small images. Proc. 2013 IEEE Int. Conf. Green Computing and Communications and IEEE Internet of Things and IEEE Cyber Physical and Social Computing, 2231–2234, 2013.
- Che, H.; Zhang, H. Exploiting fastDFS client-based small file merging. Proc. 2016 Int. Conf. Artificial Intelligence and Engineering Applications, 242–246, 2016.
- Ullah, Z.; Jabbar, S.; Bin, M.H.; Alvi, T.; Ahmad, A. Analytical study on performance challenges and future considerations of Google file system. Int. J. Computer Communicat. Eng., 3, 279–284, 2014.