EvalNet: A Practical Toolchain for Generation and Analysis of Extreme-Scale Interconnects

TL;DR

EvalNet is a comprehensive toolchain for generating and analyzing diverse network topologies at extreme scales, providing detailed insights into path diversity, performance metrics, and resource costs.

Contribution

It introduces EvalNet, a novel toolchain capable of large-scale network topology analysis with detailed path diversity and performance modeling features.

Findings

Wide-ranging analysis of over 25 network topologies.

Demonstrates the importance of path diversity for throughput and scalability.

Provides detailed models for construction cost and power consumption.

Abstract

The diversity of communication paths in a network, especially non-minimal paths, is a key enabler of performance at extreme scales. We present EvalNet, a toolchain for scalable generation and analysis of over 25 important network topologies, such as Slim Fly, PolarFly, and Orthogonal Fat Trees, with a strong focus on path diversity metrics. EvalNet provides an extensive and fine-grained analysis of shortest and non-shortest paths, including their multiplicities, lengths, and interference. It supports exact measurement and visualization of bandwidth and throughput between every router pair, enabling unprecedented insight into routing potential. EvalNet also includes detailed models for construction cost and power consumption, and interfaces seamlessly with established simulators, which we tune to support large-scale evaluations on low-cost hardware. Using EvalNet, we deliver the widest and most comprehensive path diversity study to date, demonstrating how path diversity underpins throughput and scalability, and facilitating progress towards new frontiers in extreme-scale network design.