Liveness-Aware Checkpointing of Arrays for Efficient Intermittent Computing
Youngbin Kim, Yoojin Lim, Chaedeok Lim · 2023
Intermittent computing enables computing under environments that may experience frequent and unpredictable power failures, such as energy harvesting systems. It relies on checkpointing to preserve computing progress between power cycles, which often incurs significant overhead due to energy-expensive writes to Non-Volatile Memory (NVM). In this paper, we present LACT (Liveness-Aware CheckpoinTing), as an approach to reducing the size of checkpointed data by exploiting the liveness of memory objects: excluding dead memory objects from checkpointing does not affect the correctness of the program. Especially, LACT can analyze the liveness of arrays, which take up most of the memory space but are not analyzable by existing methods for detecting the liveness of scalar objects. Using the liveness information of arrays, LACT determines the minimized checkpoint range for the arrays at compile time without any runtime addition. Our evaluation shows that LACT achieves an additional reduction of checkpointed data size of 37.8% on average over the existing state-of-the-art technique. Also, our experiments on a real energy harvesting environment show that LACT can reduce the execution time of applications by 27.7% on average.