Processing-Near-Memory (PNM) over Compute Express Link (CXL) has strong architectural appeal. However, most existing CXL-attached PNM prototypes remain inflexible or simulation-based and lack integration with full software stacks, which limits their practical deployment. This work introduces CMM-Ax, a deployable hybrid CXL-PNM system that combines streaming near-memory pipelines with device-side programmability and integrates tightly with the Heterogeneous Memory Software Development Kit (HMSDK). Through HMSDK, CMM-Ax exposes CXL-attached memory via standard Linux allocation paths (e.g., malloc and mmap). This allows existing vector databases and search engines to adopt heterogeneous memory with minimal application-level changes, such as selecting the CMM-Ax FAISS backend. CMM-Ax further provides a comprehensive software stack—FAISS integration, a domain-specific compiler for user-defined operators, and a Kubernetes device plugin supporting multi-tenant slicing—capabilities not demonstrated in prior CXL-PNM. Using an FPGA-based CXL Type-3 prototype, CMM-Ax achieves 4.54× higher throughput and 5.56× lower energy per query than a CXL memory-only baseline on the exact k-nearest neighbor (kNN) search. For approximate nearest neighbor (ANN) inverted-file (IVF) workloads, CMM-Ax sustains bandwidth-proportional efficiency at small batches (batch=1: 37% vs. 12% CPU, 7% GPU). In Kubernetes deployments, CMM-Ax–equipped servers can replace a significantly larger CPU-only cluster at equivalent memory capacity and throughput, reducing node count and system energy.

Message Passing Interface (MPI) is a foundational programming model for high-performance computing. MPI libraries traditionally employ network interconnects (e.g., Ethernet and InfiniBand) and network protocols (e.g., TCP and RoCE) with complex software stacks for cross-node communication.This paper presents cMPI, the first work to optimize MPI point-to-point communication (both one-sided and two-sided) using CXL memory sharing on a real CXL platform, transforming cross-node communication into memory transactions and data copies within CXL memory, bypassing traditional network protocols. We analyze performance across various interconnects and find that CXL memory sharing achieves 7.2 × -8.1 × lower latency than TCP-based interconnects deployed in small- and medium-scale clusters. We address challenges of CXL memory sharing for MPI communication, including data object management over the dax representation [50], cache coherence, and atomic operations. Overall, cMPI outperforms TCP over standard Ethernet NIC and high-end SmartNIC by up to 49 × and 72 × in latency and bandwidth, respectively, for small messages.