Remote Direct Memory Access (RDMA) equips modern data centers (DCs) with high-performance data trans- mission. Yet, its potential is often unmet, as the State-Of-The-Art (SOTA) RDMA traffic load balancers struggle to balance high- performance with practicability. In this paper, we first analyse existing RDMA-aware load balancers, examining their trade-offs across four key metrics: path utilization, packet order preserva- tion, implementation overhead, and deployment complexity. We then present HP3, a host-based load balancer designed to excel in all these dimensions. HP3 combines Proactive Path Perception for real-time path state awareness with Reorder Free Rerouting to guarantee in-order packet delivery. It maintains low intrusiveness by complying with the standard RDMA transport layer and activating only during severe congestion. Implemented purely on end-hosts with no switch modifications, HP3 offers a practical solution with modest additional overhead. We prototype HP3 using DPDK and commodity RNICs, and evaluate it on a P4- programmable switch testbed. Experiments with diverse data center workloads show that HP3 outperforms SOTA RDMA load balancers by up to 3.4× for typical traffic and 1.3× for AI training traffic.

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 MultiPath (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.