Journal of Computer Science and Technology ›› 2020, Vol. 35 ›› Issue (1): 121-144.doi: 10.1007/s11390-020-9802-0

Special Issue: Computer Architecture and Systems

• Special Section on Selected I/O Technologies for High-Performance Computing and Data Analytics • Previous Articles     Next Articles

Mochi: Composing Data Services for High-Performance Computing Environments

Robert B. Ross1, George Amvrosiadis2, Philip Carns1, Charles D. Cranor2, Matthieu Dorier1, Kevin Harms1, Greg Ganger2, Garth Gibson3, Samuel K. Gutierrez4, Robert Latham1, Bob Robey4, Dana Robinson5, Bradley Settlemyer4, Galen Shipman4, Shane Snyder1, Jerome Soumagne5, Qing Zheng2   

  1. 1 Argonne National Laboratory, Lemont, IL 60439, U.S.A;
    2 Parallel Data Laboratory, Carnegie Mellon University, Pittsburgh, PA 15213, U.S.A;
    3 Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada;
    4 Los Alamos National Laboratory, Los Alamos NM, U.S.A;
    5 The HDF Group, Champaign IL, U.S.A
  • Received:2019-07-01 Revised:2019-11-02 Online:2020-01-05 Published:2020-01-14
  • About author:Robert B. Ross is a senior computer scientist at Argonne National Laboratory, Lemont, and a senior fellow at the Northwestern-Argonne Institute for Science and Engineering at Northwestern University, Evanston. Dr. Ross's research interests are in system software and architectures for high-performance computing and data analysis systems, in particular storage systems and software for I/O and message passing. Rob received his Ph.D. degree in computer engineering from Clemson University in 2000. Rob was a recipient of the 2004 Presidential Early Career Award for Scientists and Engineers.
  • Supported by:
    This work is in part supported by the Director, Office of Advanced Scientific Computing Research, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357; in part supported by the Exascale Computing Project under Grant No. 17-SC-20-SC, a joint project of the U.S. Department of Energy's Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation's exascale computing imperative; and in part supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Scientific Discovery through Advanced Computing (SciDAC) program.

Technology enhancements and the growing breadth of application workflows running on high-performance computing (HPC) platforms drive the development of new data services that provide high performance on these new platforms, provide capable and productive interfaces and abstractions for a variety of applications, and are readily adapted when new technologies are deployed. The Mochi framework enables composition of specialized distributed data services from a collection of connectable modules and subservices. Rather than forcing all applications to use a one-size-fits-all data staging and I/O software configuration, Mochi allows each application to use a data service specialized to its needs and access patterns. This paper introduces the Mochi framework and methodology. The Mochi core components and microservices are described. Examples of the application of the Mochi methodology to the development of four specialized services are detailed. Finally, a performance evaluation of a Mochi core component, a Mochi microservice, and a composed service providing an object model is performed. The paper concludes by positioning Mochi relative to related work in the HPC space and indicating directions for future work.

Key words: storage and I/O, data-intensive computing, distributed services, high-performance computing

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