Arcal\'{i}s: Accelerating Remote Procedure Calls Using a L\'{i}ghtweight Near-Cache Solution
Modern microservices increasingly depend on high-performance remote procedure calls (RPCs) to coordinate fine-grained, distributed computation. As network bandwidths continue to scale, the CPU overhead associated with RPC processing, particularly serialization, deserialization, and protocol handling, has become a critical bottleneck. This challenge is exacerbated by fast user-space networking stacks such as DPDK, which expose RPC processing as the dominant performance limiter. While prior hardware accelerators have explored NIC-attached and FPGA-based offload, these approaches remain farther from the cache hierarchy, so the frequent data accesses during RPC processing each pay an extra interconnect traversal cost that inflates RPC time. Therefore, RPC handling should occur as close as possible to the cache; however, a near-cache solution must be small, hence practical and deployable. Our key insight to enable such a solution is taking advantage of a reconfigurable accelerator that can be configured specifically for the services currently running on the CPUs. We present Arcal\'{\i}s, a near-cache RPC accelerator that positions a lightweight hardware engine adjacent to the last-level cache (LLC). Arcal\'{\i}s offloads RPC processing to dedicated microengines that operate with cache-line latency while preserving programmability. By decoupling RPC processing logic, enabling microservice-specific execution, and positioning itself near the LLC, Arcal\'{\i}s achieves a 1.72-4.91$\times$ end-to-end speedup compared to the CPU baseline, significantly reduces microarchitectural overhead by up to 88\%, and achieves up to a 1.62$\times$ higher throughput than prior solutions. These results highlight the potential of near-cache RPC acceleration as a practical solution for high-performance microservice deployment.