Innovative Techniques in the Construction of Very Large Scale Integration Circuits for Low-Power and High-Performance Circuits

Portable electronic gadgets and high-performance computing systems have increased demand for low-power, high-performance integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to millions of transistors on a chip, is leading these efforts. This research investigate...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2024 Global Conference on Communications and Information Technologies (GCCIT) s. 1 - 6
Hlavní autoři: Saravanan, V., Sasikala, G., Gomathi, P., Kirubakaran, D., Rajalingam, A., Pagunuran, Jubert R.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 25.10.2024
Témata:
Adaptive Body Biasing
Clock Tree Optimization
Design Automation
Design methodology
Emerging Materials and Device Structures
Leakage currents
Machine learning
Machine Learning in VLSI Design
Performance evaluation
Power Gating
Process Variation
Routing
Signal integrity
Signal Integrity Enhancement
Thermal management
Timing
Topology
Very large scale integration
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Portable electronic gadgets and high-performance computing systems have increased demand for low-power, high-performance integrated circuits (ICs). VLSI technology, which creates integrated circuits with dozens to millions of transistors on a chip, is leading these efforts. This research investigates low-power, high-performance VLSI circuit construction methods. We start with VLSI design fundamentals and power management and performance optimization concerns. The constraints of traditional VLSI design methods in satisfying current electronics' strict requirements are examined. VLSI design methodology development and evaluation are the focus of this research. Advanced power optimization methods include MTCMOS, adaptive body biasing, and power gating. We also study clock tree improvement, signal integrity enhancement, and new materials and device topologies for high performance. In addition, we study how machine learning techniques automate and optimize circuit placement, routing, and timing in VLSI design. AI handles the complexity of current VLSI designs and finds optimal design parameters for minimal power and high performance. Scaling VLSI circuits to newer technology nodes raises process variance, leakage current, and thermal management difficulties, which the research tackles. These issues can be overcome with new ways to keep VLSI circuits scaling while preserving performance and power efficiency. Finally, case studies and experimental findings show that the offered methods work in real-world applications. These findings demonstrate significant power usage and performance benefits over typical VLSI design. In conclusion, our research advances VLSI technology by developing low-power, high-performance integrated circuits. The proposed VLSI design methods and solutions could lead to more efficient and powerful electronic systems.
DOI:10.1109/GCCIT63234.2024.10862370