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Yongqiang Xiong

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Book Open access Aug 2026

PIN: Less Is More for RDMA Load Balancing

As RDMA becomes increasingly tolerant to out-of-order delivery, fine-grained packet-level multipathing is emerging as a practical design for datacenter fabrics. Packet spraying and related schemes improve load distribution for large flows, but they also force RDMA flows onto multiple paths whose conditions can differ at short timescales due to randomized traffic placement. For short flows, even one packet sent on a temporarily slower path can delay the entire flow. As a result, fine-grained load balancing can hurt, rather than help, small multi-packet flows. We present PIN, a lightweight wrapper that layers on top of any existing fine-grained RDMA load balancer. PIN applies less multipathing to short flows, which benefit from it least: it pins short flows to one path for their lifetime and leaves larger flows to the baseline mechanism. The design is simple, compositional, and requires only a size threshold. We show analytically that practical thresholds preserve overall load-balance fairness while reducing short-flow exposure to temporarily slower paths. Large-scale simulations across a variety of workloads show that PIN consistently improves both mean and tail completion time for short flows across multiple RDMA load-balancing baselines.

Jichun Wu, Ran Shu, A. Moore et al. · 0 citations
Book Open access Aug 2026

Nüwa: A Generative Control Plane for AI Network Simulation

Nüwa is presented, which views routing as a compilation problem, it leverages the hierarchical and symmetric structure common in AI fabrics and compiles a declarative topology description together with routing policies into compact forwarding artifacts that are fast to generate and efficient to look up.

Wenkai Li, Ran Shu, Peng Zhang et al. · 0 citations
Book Open access Aug 2026

OptiFlow: Towards LLM-Driven Optimization of Collective Communication Algorithms

OptiFlow is presented, among the first LLM-driven frameworks for automated design of high-performance collective communication algorithms, with key insight is a two-layer decomposition: the LLM generates compact data-movement intent expressed in a domain-specific language, while deterministic scheduling algorithms compile these programs into executable schedules.

Fei Long, Ziyue Yang, Kaihui Gao et al. · 1 citation
Book Open access Aug 2026

STORM: Enabling Traffic Scheduling for RDMA

STORM is presented, a NIC-level scheduler for all types of RDMA workloads using NIC-only information: the known RDMA request size, and per-queue-pair backlog, and converts these signals into a small number of extra priority levels on the wire and prioritizes requests that are either near completion or blocking queued dependent work.

Jichun Wu, Ran Shu, Gianni Antichi et al. · 0 citations

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