For promising performance boost, recent trends of modern data centers tend to use Persistent Memory (PM) as storage and utilize the one-sided feature of Remote Direct Memory Access (RDMA) to directly access PM for I/O requests. However, accessing PM through one-sided RDMA faces two challenges: one-sided data races and remote data crash consistency. Existing systems that employ server-bypass mechanism either abandon server-bypass write to avoid the challenges at the cost of extra server loads, or support both server-bypass read/write through inefficient concurrency control without ensuring remote crash consistency. In this paper, we propose a novel server-bypass RDMA-to-PM framework, named Forca, to provide high concurrency and guarantee remote crash consistency at the same time. In Forca, we design an optimized log-structured mechanism to eliminate in-place updates, removing race conditions of one-sided RDMA and providing atomicity for each update simultaneously. We implement Forca as a generic module to support server-bypass RDMA to PM, and conduct experiments on a Forca-based key-value store called ForcaKV. The experiments show that Forca achieves higher throughput than state-of-the-art techniques by up to 1.4x under high concurrency scenarios, and its crash consistency mechanism incurs only 14.7%-19.1% time overhead.