Building and utilizing fault tolerance support tools for the GASPI applications. (September 2018)

• Record Type: Journal Article
• Authors: Shahzad, Faisal; Kreutzer, Moritz; Zeiser, Thomas; Machado, Rui; Pieper, Andreas; Hager, Georg; Wellein, Gerhard
• Other Names: Bland Wesley guest-editor.; Erez Mattan guest-editor.; Hidalgo J Ignacio guest-editor.; Fernández de Vega Francisco guest-editor.; Mercier Guillaume guest-editor.
• Is Part Of: International journal of high performance computing applications. Volume 32:Number 5(2018)
• Page Start: 613
• Page End: 626
• Publication Date: 2018-09
• Subjects: GASPI -- Global address space Programming Interface (GPI2) -- fault tolerance -- fault detection -- health-check library -- node-level checkpoint-restart -- fault-tolerant iterative solvers; High performance computing -- Periodicals; Supercomputers -- Periodicals; 004.1105
• DOI: 10.1177/1094342016677085
• Languages: English
• ISSNs: 1094-3420

Abstract

Today's high performance computing systems are made possible by multiple increases in hardware parallelity. This results in the decrease of mean time to failures of the systems with each newer generation, which is an alarming trend. Therefore, it is not surprising that a lot of research is going on in the area of fault tolerance and fault mitigation. Applications should survive a failure and/or be able to recover with minimal cost. We have used Global Address Space Programming Interface (GASPI), which is a relatively new communication library based on the PGAS model. It fulfills the basic requirement of a fault tolerant communication library, i.e. the failure of a process does not cause the remaining processes to fail. This work is focused on extending the fault tolerance features of GASPI in the form of a supporting health-check library that applications can benefit from. These features include failure detection, its information propagation, recovery management, communication recovery, etc. To reinforce its utility, we have also developed a fault tolerant neighbor node-level checkpoint/restart library. Instead of introducing algorithm-based fault tolerance in its true sense, we demonstrate how (using these supplementary fault tolerance functions) one can build applications to allow integrate a low cost fault detection/recovery mechanism and, if necessary, recover the application on the fly. We showcase the usage of these tools by implementing them in three different applications. Two of the applications fall in the category of linear sparse solvers, whereas the third application is based on a fluid flow solver. We also analyze the overheads involved in failure-free cases as well as various failure cases. Our fault detection mechanism causes no overhead in failure-free cases, whereas in case of failure(s), the failure detection and recovery cost is of reasonably acceptable order and shows good scalability.