MetaSys: A Practical Open-Source Metadata Management System to Implement and Evaluate Cross-Layer Optimizations

TL;DR

MetaSys is an open-source FPGA-based infrastructure that enables rapid implementation and evaluation of diverse cross-layer hardware-software optimization techniques in real hardware, demonstrated through three practical use cases.

Contribution

MetaSys introduces a versatile, lightweight metadata management system with a rich hardware-software interface, facilitating quick deployment and evaluation of cross-layer techniques in CPUs.

Findings

MetaSys supports three diverse cross-layer techniques with minimal code (~100 lines).

It enables detailed performance overhead analysis of metadata management in CPUs.

MetaSys improves efficiency and versatility over previous systems.

Abstract

This paper introduces the first open-source FPGA-based infrastructure, MetaSys, with a prototype in a RISC-V core, to enable the rapid implementation and evaluation of a wide range of cross-layer techniques in real hardware. Hardware-software cooperative techniques are powerful approaches to improve the performance, quality of service, and security of general-purpose processors. They are however typically challenging to rapidly implement and evaluate in real hardware as they require full-stack changes to the hardware, OS, system software, and instruction-set architecture (ISA). MetaSys implements a rich hardware-software interface and lightweight metadata support that can be used as a common basis to rapidly implement and evaluate new cross-layer techniques. We demonstrate MetaSys's versatility and ease-of-use by implementing and evaluating three cross-layer techniques for: (i) prefetching for graph analytics; (ii) bounds checking in memory unsafe languages, and (iii) return address protection in stack frames; each technique only requiring ~100 lines of Chisel code over MetaSys. Using MetaSys, we perform the first detailed experimental study to quantify the performance overheads of using a single metadata management system to enable multiple cross-layer optimizations in CPUs. We identify the key sources of bottlenecks and system inefficiency of a general metadata management system. We design MetaSys to minimize these inefficiencies and provide increased versatility compared to previously-proposed metadata systems. Using three use cases and a detailed characterization, we demonstrate that a common metadata management system can be used to efficiently support diverse cross-layer techniques in CPUs.