Arista's Etherlink AI Platform: AI-based Network Architecture Designed for High-Performance AI Workloads, Focusing on Congestion Avoidance and Optimized Ethernet Utilization
Independent Researcher, Yondertech Dallas, Texas, USA, Santhosh Katragadda, Odubade Kehinde, Independent Researcher, Yondertech Dallas, Texas, USA, Jonathan Goh, Independent Researcher, Yondertech Dallas, Texas, USA · International Journal of Multidisciplinary Research in Science, Engineering and Technology. · 2021
The rapid expansion of artificial intelligence (AI) and machine learning (ML) workloads has created an urgent demand for high-performance, low-latency network architectures capable of handling massive data transfers with minimal congestion. Traditional Ethernet solutions often struggle with inefficiencies, packet loss, and network congestion, limiting AI scalability and performance. Arista’s Etherlink AI platform introduces an advanced AIoptimized Ethernet architecture designed to enhance congestion avoidance, maximize bandwidth utilization, and provide lossless data transmission for high-performance computing environments. By integrating real-time telemetry, intelligent packet scheduling, and adaptive routing mechanisms, Etherlink AI ensures optimal network efficiency, enabling seamless AI workload execution. This paper examines the platform’s core architectural components, congestion control strategies, and impact on next-generation AI infrastructure, highlighting its role in addressing the critical challenges of modern AI-driven networking.