Next-Generation FPGA Architectures Through Balancing Performance, Flexibility, and Power Consumption
Background: Field-Programmable Gate Arrays (FPGAs) play a crucial role in developing contemporary computing architectures, providing unmatched versatility in hardware design. Nevertheless, the rapid growth in computational requirements calls for improved FPGA architectures that fulfil performance criteria and maximize power economy. Objective: The article aims to investigate the advancement of next-generation FPGA architectures that attain an ideal equilibrium between performance, adaptability, and power usage. The goal is to provide a structure that aids in the strategic choices that impact FPGA design and create sustainable and efficient computing solutions. Methods: We used a comparative analysis methodology to investigate several FPGA architectures to discover the primary parameters impacting performance and power consumption. The study combines simulations and real-world testing scenarios to assess the effect of various design techniques on the operational efficiency of FPGAs. Results: The results demonstrate that including adaptive routing techniques and heterogeneous integration greatly improves performance while decreasing power consumption. Advanced power gating approaches and dynamic frequency scaling have become essential for reducing energy consumption while maintaining the flexibility provided by conventional FPGAs. Conclusion: The study's findings suggest that by strategically including adaptive design components and power management approaches, next-generation FPGA designs can achieve a harmonious balance between performance, adaptability, and power consumption. These developments facilitate the development of computing platforms that are more environmentally friendly and can meet the increasing requirements of high-performance applications.
Authors
- Mohammed Shakir
- Saja Abdulfattah Salih
- Salam Hussein Yahya
- Maher Abedah
- Nabaa Ahmed Noori (ORCID: https://orcid.org/0009-0001-3091-9734)
Institutions
- Al-Turath University (IQ)
- Alsalam University College (IQ)
- Al Mansour University College (IQ)
- Al-Nisour University College (IQ)
Publication Details
- Journal
- Radioelectronics Nanosystems Information Technologies
- Published
- 2024-09-06
- DOI
- https://doi.org/10.17725/j.rensit.2024.16.673
- Primary Topic
- Low-power high-performance VLSI design
- Type
- article
- Field-Weighted Citation Impact
- 0.00