CHERI Performance Enhancement for a Bytecode Interpreter

Lowther, D. , Jacob, D. and Singer, J. (2023) CHERI Performance Enhancement for a Bytecode Interpreter. In: VMIL '23: Proceedings of the 15th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages, Cascais, Portugal, 23 October 2023, pp. 1-10. ISBN 9798400704017 (doi: 10.1145/3623507.3623552)

Abstract

During our port of the MicroPython bytecode interpreter to the CHERI-based Arm Morello platform, we encountered a number of serious performance degradations. This paper explores several of these performance issues in detail, in each case we characterize the cause of the problem, the fix, and the corresponding interpreter performance improvement over a set of standard Python benchmarks. While we recognize that Morello is a prototypical physical instantiation of the CHERI concept, we show that it is possible to eliminate certain kinds of software-induced runtime overhead that occur due to the larger size of CHERI capabilities (128 bits) relative to native pointers (generally 64 bits). In our case, we reduce a geometric mean benchmark slowdown from 5x (before optimization) to 1.7x (after optimization) relative to AArch64, non-capability, execution. The worst-case slowdowns are greatly improved, from 100x (before optimization) to 2x (after optimization). The key insight is that implicit pointer size presuppositions pervade systems code; whereas previous CHERI porting projects highlighted compile-time and execution-time errors exposed by pointer size assumptions, we instead focus on the performance implications of such assumptions.

• Item Type: Conference Proceedings
• Additional Information: This work was funded in part by EPSRC EP/V000349/1 and EP/X015831/1 and partly by DASA / Dstl.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lowther, Mr Duncan and Singer, Dr Jeremy and Jacob, Dr Dejice
• Authors: Lowther, D., Jacob, D., and Singer, J.
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 9798400704017
• Copyright Holders: © 2023 Copyright held by the owner/author(s)
• First Published: First published in VMIL 2023: Proceedings of the 15th ACM SIGPLAN International Workshop on Virtual Machines and Intermediate Languages
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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• Pre-print

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
310130		Capable VMs	Jeremy Singer	Engineering and Physical Sciences Research Council (EPSRC)	EP/V000349/1	Computing Science
316845		Capabilities for Coders	Jeremy Singer	Engineering and Physical Sciences Research Council (EPSRC)	EP/X015831/1	Computing Science