Arcalis: Accelerating Remote Procedure Calls Using a Lightweight Near-Cache Solution

2026-02-13

Technology Category

• Machine Learning: Hardware-aware ML
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

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 work has explored software optimizations and FPGA-based offload engines, these approaches remain physically distant from the CPU's memory hierarchy, incurring unnecessary data movement and cache pollution. We present Arcalis, a near-cache RPC accelerator that positions a lightweight hardware engine adjacent to the last-level cache (LLC). Arcalis offloads RPC processing to dedicated microengines on receive and transmit paths that operate with cache-line latency while preserving programmability. By decoupling RPC processing logic, enabling microservice-specific execution, and positioning itself near the LLC to immediately consume data injected by network cards, Arcalis achieves 1.79-4.16$\times$ end-to-end speedup compared to the CPU baseline, while significantly reducing 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.

Problem

• Remote Procedure Calls
• Microservices
• CPU overhead
• Serialization
• Near-cache

Innovation

• near-cache acceleration
• RPC offloading
• microservices
• hardware-software co-design
• last-level cache