The rapid growth of AI models is placing unprecedented pressure on switch ASIC memory allocated for telemetry and flow monitoring. In this poster, we argue that the predictability of AI/ML traffic patterns can be exploited by perfect hashing techniques for accurate flow- and packet-tracking with minimal memory overhead.
POSTER: Beyond Probabilistic Data Structures for AI/ML Workload Monitoring
Palmiotti, Davide;Antichi, Gianni
2026-01-01
Abstract
The rapid growth of AI models is placing unprecedented pressure on switch ASIC memory allocated for telemetry and flow monitoring. In this poster, we argue that the predictability of AI/ML traffic patterns can be exploited by perfect hashing techniques for accurate flow- and packet-tracking with minimal memory overhead.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
