Accelerating Checkpoint Operation by Node-Level Write Aggregation on Multicore Systems

TL;DR: This work explores the Checkpoint/Restart mechanism in MVAPICH2, which uses BLCR as the checkpointing library, and proposes to optimize checkpoint creation by classifying checkpoint file writes into small writes, medium writes and large writes based on their size of data to write, and use write aggregation to optimize the small and medium writes.

Abstract: Clusters and applications continue to grow in size while their mean time between failure (MTBF) is getting smaller. Checkpoint/Restart is becoming increasingly important for large scale parallel jobs. However, the performance of the Checkpoint/Restart mechanism does not scale well with increasing job size due to constraints within the file system. Furthermore, with the advent of multi-core architecture, the situation is aggravated due to larger number of processes running on the same node, trying to checkpoint simultaneously. This results in increased number of file writes at the time of checkpointing which leads to performance degradation. As a result, deployment of Checkpoint/Restart mechanisms for large scale parallel applications is limited. In this work, we explore the Checkpoint/Restart mechanism in MVAPICH2, which uses BLCR as the checkpointing library. Our profiling of the checkpoints for the NAS parallel benchmarks revealed a large number of small file writes interspersed with large writes. Based on these observation we propose to optimize checkpoint creation by classifying checkpoint file writes into small writes, medium writes and large writes based on their size of data to write, and use write aggregation to optimize the small and medium writes. At the aggregation threshold of 512KB, the implementation of our design in BLCR shows improvements from 27% to 32% over the original BLCR in terms of time cost to checkpoint an MPI application.