ExaHDF5: Delivering Efficient Parallel I/O on Exascale Computing Systems

Journal Article · Fri Jan 17 00:00:00 EST 2020 · Journal of Computer Science and Technology

DOI:https://doi.org/10.1007/s11390-020-9822-9· OSTI ID:1582374

Byna, Suren ^[1]; Breitenfeld, M. Scot ^[2]; Dong, Bin ^[1]; Koziol, Quincey ^[1]; Pourmal, Elena ^[2]; Robinson, Dana ^[2]; Soumagne, Jerome ^[2]; Tang, Houjun ^[1]; Vishwanath, Venkatram ^[3]; Warren, Richard ^[2]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2. The HDF Group, Champaign, IL (United States)
3. Argonne National Lab. (ANL), Lemont, IL (United States)

Scientific applications at exascale generate and analyze massive amounts of data. A critical requirement of these applications is the capability to access and manage this data efficiently on exascale systems. As such, parallel I/O, the key technology enables moving data between compute nodes and storage, faces monumental challenges from new applications, memory, and storage architectures considered in the designs of exascale systems. As the storage hierarchy is expanding to include node-local persistent memory, burst buffers, etc., as well as disk-based storage, data movement among these layers must be efficient. Parallel I/O libraries of the future should be capable of handling file sizes of many terabytes and beyond. In this paper, we describe new capabilities we have developed in Hierarchical Data Format version 5 (HDF5), the most popular parallel I/O library for scientific applications. HDF5 is one of the most used libraries at the leadership computing facilities for performing parallel I/O on existing HPC systems. The state-of-the-art features we describe include: Virtual Object Layer (VOL), Data Elevator, asynchronous I/O, full-featured single-writer and multiple-reader (Full SWMR), and parallel querying. In this paper, we introduce these features, their implementations, and the performance and feature benefits to applications and other libraries.

• Research Organization: Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities Division
• Grant/Contract Number: AC02-05CH11231; 17-SC-20-SC; AC02-06CH11357
• OSTI ID: 1582374
• Journal Information: Journal of Computer Science and Technology, Vol. 35, Issue 1; ISSN 1000-9000
• Publisher: Springer Nature
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
parallel I/O
Hierarchical Data Format version 5 (HDF5)
I/O performance
virtual object layer
HDF5 optimizations