Difference between revisions of "Correctness 2017"

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{{Event  
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{{Event
|Acronym=Correctness 2017  
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|Acronym=Correctness 2017
|Title=Correctness  2017 : First International Workshop on Software Correctness for HPC Applications  
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|Title=Correctness  2017 : First International Workshop on Software Correctness for HPC Applications
|Type=Workshop  
+
|Type=Workshop
 
|Field=formal methods
 
|Field=formal methods
 
|Start date=2017/11/12
 
|Start date=2017/11/12
|End date=2017/11/12  
+
|End date=2017/11/12
|City=Denver
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|Submission deadline=2017/08/18
|Country= Colorado
 
 
|Homepage=https://correctness-workshop.github.io/2017/
 
|Homepage=https://correctness-workshop.github.io/2017/
|Submission deadline=2017/08/18
+
|City=Denver
 +
|State=Colorado
 +
|Country=USA
 
}}
 
}}
 
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Latest revision as of 17:00, 18 February 2021

Correctness 2017
Correctness 2017 : First International Workshop on Software Correctness for HPC Applications
Dates 2017/11/12 (iCal) - 2017/11/12
Homepage: https://correctness-workshop.github.io/2017/
Location
Location: Denver, Colorado, USA
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Important dates
Submissions: 2017/08/18
Table of Contents


============================================================

CALL FOR PAPERS

First International Workshop on Software Correctness for HPC Applications (Correctness 2017)

In conjunction with SC17: The International Conference for High Performance Computing, Networking, Storage and Analysis, November 12, 2017, Denver, Colorado, USA. In cooperation with SIGHPC.

https://correctness-workshop.github.io/2017/

============================================================

Scope

=

Ensuring correctness in high-performance computing (HPC) applications is one of the fundamental challenges that the HPC community faces today. While significant advances in verification, testing, and debugging have been made to isolate software errors (or defects) in the context of non-HPC software, several factors make achieving correctness in HPC applications and systems much more challenging than in general systems software: growing heterogeneity (architectures with CPUs, GPUs, and special purpose accelerators), massive scale computations (very high degree of concurrency), use of combined parallel programing models (e.g., MPI+X), new scalable numerical algorithms (e.g., to leverage reduced precision in floating-point arithmetic), and aggressive compiler optimizations/transformations are some of the challenges that make correctness harder in HPC.

As the complexity of future architectures, algorithms, and applications in HPC increases, the ability to fully exploit exascale systems will be limited without correctness. With the continuous use of HPC software to advance scientific and technological capabilities, novel techniques and practical tools for software correctness in HPC are invaluable.

The goal of the Correctness Workshop is to bring together researchers and developers to present and discuss novel ideas to address the problem of correctness in HPC. The workshop will feature contributed papers and invited talks in this area.

Topics

==

Topics of interest include, but are not limited to:

  • Formal methods and rigorous mathematical techniques for correctness

in HPC applications/systems

  • Frameworks to address the challenges of testing complex HPC

applications (e.g., multiphysics applications)

  • Approaches for the specification of numerical algorithms with the

goal of correctness checking

  • Error identification in the design and implementation of numerical

algorithms using finite-precision floating point numbers

  • Static and dynamic analysis to test and check correctness in the

entire HPC software ecosystem

  • Practical and scalable tools for model checking, verification,

certification, or symbolic execution

  • Analysis of error propagation and error handling in HPC libraries
  • Techniques to control the effect of non-determinism when debugging

and testing HPC software

  • Scalable debugging solutions for large-scale HPC applications
  • Predictive debugging and testing approaches to forecast the

occurrence of errors in specific conditions

  • Machine learning and anomaly detection approaches for bug detection

and localization

  • Metrics to measure the degree of correctness of HPC

applications/systems

  • Community-wide models to share past successes (e.g., bug report

databases, reproducible test cases)

Dates

=

Paper submissions due: August 18, 2017 Notification of acceptance: September 15, 2017 Camera-ready papers due (firm): October 6, 2017 Workshop: SC 2017, Sun, Nov 12 (at 9am-12:30pm), 2017

Organizers

==

Ignacio Laguna, LLNL Cindy Rubio-González, UC Davis

Program Committee

=====

David Abramson, The University of Queensland, Australia Eva Darulova, MPI-SWS, Germany Alastair Donaldson, Imperial College London, UK Ganesh Gopalakrishnan, University of Utah, USA Paul Hovland, ANL, USA Costin Iancu, LBNL, USA Sriram Krishnamoorthy, PNNL, USA David Lecomber, Allinea/ARM, UK Richard Lethin, Reservoir Labs, Yale University, USA Matthias Müller, RWTH Aachen University, Germany Feng Qin, The Ohio State University, USA Nathalie Revol, INRIA - ENS de Lyon, France Koushik Sen, UC Berkeley, USA Stephen Siegel, University of Delaware, USA Armando Solar-Lezama, MIT, USA

Contact

=

Please address workshop questions to Ignacio Laguna (ilaguna@llnl.gov) and/or Cindy Rubio-González (crubio@ucdavis.edu).

Facts about "Correctness 2017"
AcronymCorrectness 2017 +
End dateNovember 12, 2017 +
Event typeWorkshop +
Has coordinates39° 44' 21", -104° 59' 6"Latitude: 39.739236111111
Longitude: -104.98486111111
+
Has location cityDenver +
Has location countryCategory:Colorado +
Homepagehttps://correctness-workshop.github.io/2017/ +
IsAEvent +
Start dateNovember 12, 2017 +
Submission deadlineAugust 18, 2017 +
TitleCorrectness 2017 : First International Workshop on Software Correctness for HPC Applications +