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Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP)

Communications in Computer and Information Science

Heroux, Michael A.; Gonsiorowski, Elsa; Gupta, Rinku; Milewicz, Reed M.; Moulton, J.D.; Watson, Gregory R.; Willenbring, James M.; Zamora, Richard J.; Raybourn, Elaine M.

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

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TYPE Conference Poster YEAR 2020
ScopusOSTIDOI

Trust me. QED

SIAM News

Heroux, Michael A.

Consider a standard SIAM journal article containing theoretical results. Each theorem has a proof that typically builds on previous developments. Since every theorem stems from a firm foundation, the research community can trust a result without further evidence. One could thus argue that a theorem does not require a proof because surely an author would not publish it if no proof existed to back it up. Furthermore, respectable reviewers and editors expect proofs without exception, and papers containing proof-less theorems will likely go unpublished.

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TYPE Journal Article YEAR 2019
OSTI

Toward a Compatible Reproducibility Taxonomy for Computational and Computing Sciences

Heroux, Michael A.; Barba, Lorena B.; Parashar, Manish P.; Stodden, Victoria S.; Taufer, Michela T.

Reproducibility is an essential ingredient of the scientific enterprise. The ability to reproduce results builds trust that we can rely on the results as foundations for future scientific exploration. Presently, the fields of computational and computing sciences provide two opposing definitions of reproducible and replicable. In computational sciences, reproducible research means authors provide all necessary data and computer codes to run analyses again, so others can re-obtain the results (J. Claerbout et al., 1992). The concept was adopted and extended by several communities, where it was distinguished from replication: collecting new data to address the same question, and arriving at consistent findings (Peng et al. 2006). The Association of Computing Machinery (ACM), representing computer science and industry professionals, recently established a reproducibility initiative, adopting essentially opposite definitions. The purpose of this report is to raise awareness of the opposite definitions and propose a path to a compatible taxonomy.

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TYPE SAND Report YEAR 2018
OSTIDOI

Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping

SIAM Journal on Scientific Computing

Gamell, Marc G.; Teranishi, Keita T.; Kolla, Hemanth K.; Mayo, Jackson M.; Heroux, Michael A.; Chen, Jacqueline H.; Parashar, Manish P.

In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments. In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.

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TYPE Journal Article YEAR 2017
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Modeling and simulating multiple failure masking enabled by local recovery for stencil-based applications at extreme scales

IEEE Transactions on Parallel and Distributed Systems

Gamell, Marc; Teranishi, Keita T.; Mayo, Jackson M.; Kolla, Hemanth K.; Heroux, Michael A.; Chen, Jacqueline H.; Parashar, Manish

Obtaining multi-process hard failure resilience at the application level is a key challenge that must be overcome before the promise of exascale can be fully realized. Previous work has shown that online global recovery can dramatically reduce the overhead of failures when compared to the more traditional approach of terminating the job and restarting it from the last stored checkpoint. If online recovery is performed in a local manner further scalability is enabled, not only due to the intrinsic lower costs of recovering locally, but also due to derived effects when using some application types. In this paper we model one such effect, namely multiple failure masking, that manifests when running Stencil parallel computations on an environment when failures are recovered locally. First, the delay propagation shape of one or multiple failures recovered locally is modeled to enable several analyses of the probability of different levels of failure masking under certain Stencil application behaviors. Our results indicate that failure masking is an extremely desirable effect at scale which manifestation is more evident and beneficial as the machine size or the failure rate increase.

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TYPE Journal Article YEAR 2017
ScopusOSTIDOI
Results 1–25 of 186
Results 1–25 of 186