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Kolla, Hemanth

Publications and source records attributed to Kolla, Hemanth.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

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

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.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

ASC ATDM Level 2 Milestone #6015: Asynchronous Many-Task Software Stack Demonstration

This report is an outcome of the ASC ATDM Level 2 Milestone 6015: Asynchronous Many-Task Software Stack Demonstration. It comprises a summary and in depth analysis of DARMA and a DARMA-compliant Asynchronous Many-Task (AMT) runtime software stack. Herein performance and productivity of the over- all approach are assessed on benchmarks and proxy applications representative of the Sandia ATDM applications. As part of the effort to assess the perceived strengths and weaknesses of AMT models compared to more traditional methods, experiments were performed on ATS-1 (Advanced Technology Systems) test bed machines and Trinity. In addition to productivity and performance assessments, this report includes findings on the generality of DARMAs backend API as well as findings on interoperability with node- level and network-level system libraries. Together, this information provides a clear understanding of the strengths and limitations of the DARMA approach in the context of Sandias ATDM codes, to guide our future research and development in this area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Flame thickness and conditional scalar dissipation rate in a premixed temporal turbulent reacting jet

The flame structure corresponding to lean hydrogen–air premixed flames in intense sheared turbulence in the thin reaction zone regime is quantified from flame thickness and conditional scalar dissipation rate statistics, obtained from recent direct numerical simulation data of premixed temporally-evolving turbulent slot jet flames. It is found that, on average, these sheared turbulent flames are thinner than their corresponding planar laminar flames. Extensive analysis is performed to identify the reason for this counter-intuitive thinning effect. The factors controlling the flame thickness are analyzed through two different routes i.e., the kinematic route, and the transport and chemical kinetics route. The kinematic route is examined by comparing the statistics of the normal strain rate due to fluid motion with the statistics of the normal strain rate due to varying flame displacement speed or self-propagation. It is found that while the fluid normal straining is positive and tends to separate iso-scalar surfaces, the dominating normal strain rate due to self-propagation is negative and tends to bring the iso-scalar surfaces closer resulting in overall thinning of the flame. The transport and chemical kinetics route is examined by studying the non-unity Lewis number effect on the premixed flames. The effects from the kinematic route are found to couple with the transport and chemical kinetics route. In addition, the intermittency of the conditional scalar dissipation rate is also examined. It is found to exhibit a unique non-monotonicity of the exponent of the stretched exponential function, conventionally used to describe probability density function tails of such variables. As a result, the non-monotonicity is attributed to the detailed chemical structure of hydrogen-air flames in which heat release occurs close to the unburnt reactants at near free-stream temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Achieving algorithmic resilience for temporal integration through spectral deferred corrections

Spectral deferred corrections (SDC) is an iterative approach for constructing higher-order-accurate numerical approximations of ordinary differential equations. SDC starts with an initial approximation of the solution defined at a set of Gaussian or spectral collocation nodes over a time interval and uses an iterative application of lower-order time discretizations applied to a correction equation to improve the solution at these nodes. Each deferred correction sweep increases the formal order of accuracy of the method up to the limit inherent in the accuracy defined by the collocation points. In this paper, we demonstrate that SDC is well suited to recovering from soft (transient) hardware faults in the data. A strategy where extra correction iterations are used to recover from soft errors and provide algorithmic resilience is proposed. Specifically, in this approach the iteration is continued until the residual (a measure of the error in the approximation) is small relative to the residual of the first correction iteration and changes slowly between successive iterations. Here, we demonstrate the effectiveness of this strategy for both canonical test problems and a comprehensive situation involving a mature scientific application code that solves the reacting Navier-Stokes equations for combustion research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Scalability of Several Asynchronous Many-Task Models for In Situ Statistical Analysis.

This report is a sequel to [PB16], in which we provided a first progress report on research and development towards a scalable, asynchronous many-task, in situ statistical analysis engine using the Legion runtime system. This earlier work included a prototype implementation of a proposed solution, using a proxy mini-application as a surrogate for a full-scale scientific simulation code. The first scalability studies were conducted with the above on modestly-sized experimental clusters. In contrast, in the current work we have integrated our in situ analysis engines with a full-size scientific application (S3D, using the Legion-SPMD model), and have conducted nu- merical tests on the largest computational platform currently available for DOE science ap- plications. We also provide details regarding the design and development of a light-weight asynchronous collectives library. We describe how this library is utilized within our SPMD- Legion S3D workflow, and compare the data aggregation technique deployed herein to the approach taken within our previous work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization: An Interim Report of Sandia Sub-Team Contributions

As we look ahead to next generation high performance computing platforms, the placement and movement of data is becoming the key-limiting factor on both performance and energy efficiency. Furthermore, the increased quantities of data the systems are capable of generating, in conjunction with the insufficient rate of improvements in the supporting I/0 infrastructure, is forcing applications away from the off-line post-processing of data towards techniques based on in ,situ analysis and visualization. Together, these challenges are shaping how we will both design and develop effective, performant and energy-efficient software. In particular, the challenges highlight the need for data and data-centric operations to be fundamental in the reasoning about, and optimization of, scientific workflows on extreme-scale architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Modeling and Simulating Multiple Failure Masking enabled by Local Recovery for Stencil-based Applications at Extreme Scales

By 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. Some 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. These 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.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

DARMA v. Beta 0.5

DARMA is a portability layer for asynchronous many-task (AMT) runtime systems. AMT runtime systems show promise to mitigate challenges imposed by next generation high performance computing architectures. However, current runtime system technologies are not production-ready. DARMA is a portability layer that seeks to insulate application developers from idiosyncrasies of individual runtime systems, thereby facilitating application-developer use of these technologies. DARMA comprises a frontend application programming interface (API) for application developers, a backend API for runtime system developers, and a translation that translates frontend API calls into backend API calls. Application developers use C++ abstractions to annotate both data and tasks in their code. The DARMA translation layer uses C++ template metaprogramming to capture data-task dependencies, and provides this information to a potential backend runtime system via a series of backend API calls.

Hollman, David↗