Thermal analysis of multiprocessor SoC applications by simulation and verification

Abstract

Overheating of computer chips leads to degradation of performance and reliability. Therefore, preventing chips from overheating in spite of increased performance requirements has emerged as a major challenge. Since the cost of cooling has been rising steadily, various architecture and application design techniques are used to prevent chip overheating. Temperature-aware task scheduling has emerged as an important application design methodology for addressing this problem in multiprocessor SoC systems. In this work we present the formulation and implementation of a method for analyzing the thermal (chip heating) behavior of a MPSoC task schedule, during the early stages of the design. We highlight the challenges in developing such a framework and propose solutions for tackling them. Due to nondeterminism in task execution times and decision branches, multiprocessor applications cannot be evaluated accurately by the current state-of-the-art thermal simulation and steady-state analysis methods. Hence an analysis covering nondeterministic execution behaviors is required for thermal analysis of MPSoC task schedules. To address this issue we propose a model checking-based approach for solving the thermal analysis problem and formulate it as a hybrid automata reachability verification problem. We present an algorithm for constructing this hybrid automata given the task schedule, a set of power profiles of tasks, and the Compact Thermal Model (CTM) of the chip. Information about task power consumption is inferred from Markov chains which are learned from power profiles of tasks, obtained from simulation or emulation runs. A numerical analysis-based algorithm which uses CounterExample-Guided Abstraction Refinement (CEGAR) is developed for reachability analysis of this hybrid automata. We propose a directed simulation methodology which uses results of a time-bounded analysis of the hybrid automata modeling thermal behavior of the application, to simulate the expected worst-case execution runs of the same. The algorithms presented in this work have been implemented in a prototype tool called HeatCheck . We present experimental results and analysis of thermal behavior of a set of task schedules executing on a MPSoC system.