Chronos: Prescheduled circuit switching for LLM training

Hundreds of thousands of accelerators are used to train LLMs, with accelerators connected by packet-switched AI fabrics. In this paper, we ask if the fabric can be built entirely from time-synchronized circuit switches instead. The goal would be to reduce power, increase switching capacity, or reduce the number of network tiers.

Authors

Institutions

Publication Details

Published
2025-09-02
DOI
https://doi.org/10.1145/3748273.3749210
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Chronos: Prescheduled circuit switching for LLM training

Nick McKeown, Sundararajan Renganathan
Parallel Computing and Optimization Techniques
article

Chronos: Prescheduled circuit switching for LLM training

Nick McKeown, Sundararajan Renganathan
article en

Abstract

Hundreds of thousands of accelerators are used to train LLMs, with accelerators connected by packet-switched AI fabrics. In this paper, we ask if the fabric can be built entirely from time-synchronized circuit switches instead. The goal would be to reduce power, increase switching capacity, or reduce the number of network tiers.

Stanford University (US)
Openalex Percentile: Top 75%
Parallel Computing and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Chronos: Prescheduled circuit switching for LLM training — Nick McKeown, Sundararajan Renganathan · (2025) | TGRS Research Map | TGRS