Low-overhead Online Assessment of Timely Progress as a System Commodity (Best Presentation Award and Outstanding Paper Award)

Abstract

The correctness of safety-critical systems depends on both their logical and temporal behavior. Control-flow integrity (CFI) is a well-established and understood technique to safeguard the logical flow of safety-critical applications. But unfortunately, no established methodologies exist for the complementary problem of detecting violations of control flow timeliness. Worse yet, the latter dimension, which we term Timely Progress Integrity (TPI), is increasingly more jeopardized as the complexity of our embedded systems continues to soar. As key resources of the memory hierarchy become shared by several CPUs and accelerators, they become hard-to-analyze performance bottlenecks. And the precise interplay between software and hardware components becomes hard to predict and reason about. How to restore control over timely progress integrity? We postulate that the first stepping stone toward TPI is to develop methodologies for Timely Progress Assessment (TPA). TPA refers to the ability of a system to live-monitor the positive/negative slack—with respect to a known reference—at key milestones throughout an application’s lifespan. In this paper, we propose one such methodology that goes under the name of Milestone-Based Timely Progress Assessment or MB-TPA, for short. Among the key design principles of MB-TPA is the ability to operate on black-box binary executables with near-zero overhead and implementable on commercial platforms. To prove its feasibility and effectiveness, we propose and evaluate a full-stack implementation called Timely Progress Assessment with 0 Overhead (TPAw0v). We demonstrate its capability in providing live TPA for complex vision applications while introducing less than 0.6% overhead. Finally, we demonstrate one use case where TPA information is used to restore TPI in the presence of temporal interference over shared memory resources.

Weifan Chen

Ph.D in Computer Science

My research interests include cyber physical system and artificial intelligence.