ACOS: Arrays of Cheap Optical Switches
Daniel Amir, Ori Cohen, Jakob Krebs, Mark Silberstein

TL;DR
ACOS introduces a scalable, cost-effective optical switch architecture using low-radix switches, enabling efficient training of large language models with performance comparable to traditional networks but at lower costs.
Contribution
It presents a novel architecture that leverages low-radix optical switches for scalable, adaptable, and cost-efficient training cluster networks, overcoming limitations of high-radix switches.
Findings
ACOS matches performance of packet-switched networks for LLM training.
ACOS achieves significant cost savings with existing off-the-shelf OCSes.
The architecture supports topology adaptation and failure resilience effectively.
Abstract
Machine learning training places immense demands on cluster networks, motivating specialized architectures and co-design with parallelization strategies. Recent designs incorporating optical circuit switches (OCSes) are promising, offering improved cost, power efficiency, and long-term bandwidth scaling than packet switches. However, most existing approaches rely on costly high-radix OCSes and/or combine them with packet switches to achieve competitive performance at scale. Unfortunately, high-radix OCSes are both expensive and slow to reconfigure, limiting both scalability and performance. We propose Arrays of Cheap Optical Switches (ACOS), which bring application co-design directly to the structure of the reconfigurable fabric. Using low-radix OCSes as building blocks, ACOS supports the forms of reconfiguration needed in training clusters including topology selection, workload…
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Taxonomy
TopicsAdvanced Optical Network Technologies · Interconnection Networks and Systems · Photonic and Optical Devices
