July 2020

Conference Paper

FCP: A Fast and Scalable Data Copy Tool for High Performance Parallel File Systems

By:
Wang, Feiyi ; Melesse Vergara, Veronica G; Leverman, Dustin B; Oral, Hakki S
Journal Name:
Cray User Group (CUG) Conference Proceedings
Page Number:
1-6
Issue Number:
1
Book Title:
CUG 2016 Conference Proceedings
Publication Date:
July 2020
Conference Name:
Cray User Group (CUG) Conference Proceedings
Conference Location:
London, United Kingdom
Conference Sponsor:
Cray

Abstract

The design of HPC file and storage systems has largely been driven by the requirements on capability, reliability, and capacity. However, the convergence of large-scale simulations with big data analytics have put the data, its usability, and management back on the front and center position. One of the most common and time consuming data management tasks is the transfer of very large datasets within and across file systems. In this paper, we are introducing the FCP tool, a file system agnostic copy tool designed at the OLCF for scalable and high-performance data transfers between two file system endpoints. It provides an array of interesting features such as adaptive chunking, checksumming on the fly, checkpoint and resume capabilities to handle failures, and preserving stripe information for Lustre file system among others. It is currently available on the Titan supercomputer at the OLCF. Initial tests have shown that FCP has much better and scalable performance than traditional data copy tools and it was capable of transferring petabyte-scale datasets between two Lustre file systems.