arXiv subjects

Ahmad Ghalayini

Publications and source records attributed to Ahmad Ghalayini.

4 recordsLinked to original sources

arXiv2026

Spritz: Path-Aware Load Balancing in Low-Diameter Networks

Low-diameter topologies such as Dragonfly and Slim Fly are increasingly adopted in HPC and datacenter networks, yet existing load balancing techniques either rely on proprietary in-network mechanisms or fail to utilize the full path diversity of these topologies. We introduce Spritz, a flexible sender-based load balancing framework that shifts adaptive topology-aware routing to the endpoints using only standard Ethernet features. We propose two algorithms, Spritz-Scout and Spritz-Spray that, respectively, explore and adaptively cache efficient paths using ECN, packet trimming, and timeout feedback. Through simulation on Dragonfly and Slim Fly topologies with over 1000 endpoints, Spritz outperforms ECMP, UGAL-L, and prior sender-based approaches by up to 1.8x in flow completion time under AI training and datacenter workloads, while offering robust failover with performance improvements of up to 25.4x under link failures, all without additional hardware support. Spritz enables datacenter-scale, commodity Ethernet networks to efficiently leverage low-diameter topologies, offering unified routing and load balancing for the Ultra Ethernet era.

cs.NI↗

arXiv2026

SMaRTT: Sender-based Marked Rapidly-adapting Trimmed & Timed Transport

With the rapid growth of artificial intelligence (AI) workloads in datacenters, the Ultra Ethernet Consortium (UEC) has defined a new high-performance transport layer to deliver the required performance at scale. A core component of this new standard is the Network Signal-based Congestion Control (NSCC) algorithm. This paper presents SMaRTT, the algorithm that forms the basis of the UEC NSCC specification. SMaRTT is a sender-based congestion control algorithm that systematically combines delay, Explicit Congestion Notification (ECN), and optional packet trimming into a cohesive state machine for fast, fair and precise window adjustments with seamless multipath support. At its core lies the novel QuickAdapt algorithm that accurately estimates and rapidly adapts to available capacity. Our evaluation shows that SMaRTT outperforms existing datacenter congestion control algorithms like Swift, RoCE, and MPRDMA by up to 50% and provides superior fairness, validating the design choices made in the UEC standard.

cs.NI↗

arXiv2026

REPS: Recycled Entropy Packet Spraying for Adaptive Load Balancing and Failure Mitigation

Next-generation datacenters require highly efficient network load balancing to manage the growing scale of artificial intelligence (AI) training and general datacenter traffic. However, existing Ethernet-based solutions, such as Equal Cost Multi-Path (ECMP) and oblivious packet spraying (OPS), struggle to maintain high network utilization due to both increasing traffic demands and the expanding scale of datacenter topologies, which also exacerbate network failures. To address these limitations, we propose REPS, a lightweight decentralized per-packet adaptive load balancing algorithm designed to optimize network utilization while ensuring rapid recovery from link failures. REPS adapts to network conditions by caching good-performing paths. In case of a network failure, REPS re-routes traffic away from it in less than 100 microseconds. REPS is designed to be deployed with next-generation out-of-order transports, such as Ultra Ethernet, and uses less than 25 bytes of per-connection state regardless of the topology size. We extensively evaluate REPS in large-scale simulations and FPGA-based NICs.

cs.NI↗

arXiv2025

Uno: A One-Stop Solution for Inter- and Intra-Datacenter Congestion Control and Reliable Connectivity

Cloud computing and AI workloads are driving unprecedented demand for efficient communication within and across datacenters. However, the coexistence of intra- and inter-datacenter traffic within datacenters plus the disparity between the RTTs of intra- and inter-datacenter networks complicates congestion management and traffic routing. Particularly, faster congestion responses of intra-datacenter traffic causes rate unfairness when competing with slower inter-datacenter flows. Additionally, inter-datacenter messages suffer from slow loss recovery and, thus, require reliability. Existing solutions overlook these challenges and handle inter- and intra-datacenter congestion with separate control loops or at different granularities. We propose Uno, a unified system for both inter- and intra-DC environments that integrates a transport protocol for rapid congestion reaction and fair rate control with a load balancing scheme that combines erasure coding and adaptive routing. Our findings show that Uno significantly improves the completion times of both inter- and intra-DC flows compared to state-of-the-art methods such as Gemini.

cs.NI↗