Remote Direct Memory Access (RDMA) communication is critical for emerging cross-data-center applications. Particularly in distributed training of large AI models requiring real-time synchronization of massive parameters, as well as scientific computing and meteorological prediction fields that rely on low-latency data exchange, RDMA has become a key infrastructure supporting their core performance. However, existing RDMA technologies are constrained by critical bottlenecks such as protocol stack incompatibility, insufficient congestion control in high-latency environments, and sensitivity to packet loss, severely limiting their large-scale deployment. This paper proposes IB-APC, which extends high-performance lossless RDMA to long-distance links through a co-design of software and hardware. This technology ensures high throughput over long-distance links while achieving interoperability between InfiniBand and Ethernet. It also supports remote RDMA functionality, requiring only minimal additional switches to be added to existing intra-data-center networks. Evaluation results demonstrate that over a 500 km distance, compared to native RDMA, IB-APC achieves a 107-fold increase in bandwidth and reduces the average FCT by up to 96.2%.