Telepathic Datacenters: Fast RPCs using Shared CXL Memory
Suyash Mahar, Ehsan Hajyjasini, Seungjin Lee, Zifeng Zhang, Mingyao, Shen, and Steven Swanson

TL;DR
RPCool leverages CXL's shared memory to significantly reduce RPC latency in datacenters by avoiding serialization and efficiently managing shared data, with fallback to RDMA for scalability.
Contribution
Introduces RPCool, a novel framework that exploits CXL shared memory for fast RPCs, combining pointer sharing with safety mechanisms and RDMA fallback for scalability.
Findings
RPCool reduces round-trip latency by up to 7.2× compared to existing methods.
RPCool performs comparably or better across various workloads.
Effective memory permission management ensures safety in shared memory RPCs.
Abstract
Datacenter applications often rely on remote procedure calls (RPCs) for fast, efficient, and secure communication. However, RPCs are slow, inefficient, and hard to use as they require expensive serialization and compression to communicate over a packetized serial network link. Compute Express Link 3.0 (CXL) offers an alternative solution, allowing applications to share data using a cache-coherent, shared-memory interface across clusters of machines. RPCool is a new framework that exploits CXL's shared memory capabilities. RPCool avoids serialization by passing pointers to data structures in shared memory. While avoiding serialization is useful, directly sharing pointer-rich data eliminates the isolation that copying data over traditional networks provides, leaving the receiver vulnerable to invalid pointers and concurrent updates to shared data by the sender. RPCool restores this…
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Advanced Data Storage Technologies · Scientific Computing and Data Management
