Using Resources of Supercomputing Centers with Everest Platform

High-performance computing plays an increasingly important role in modern science and technology. However, the lack of convenient interfaces and automation tools greatly complicates the widespread use of HPC resources among scientists. The paper presents an approach to solving these problems relying on Everest, a web-based distributed computing platform. The platform enables convenient access to HPC resources by means of domain-specific computational web services, development and execution of many-task applications, and pooling of multiple resources for running distributed computations. The paper describes the improvements that have been made to the platform based on the experience of integration with resources of supercomputing centers. The use of HPC resources via Everest is demonstrated on the example of loosely coupled many-task application for solving global optimization problems.

[1]  Péter Kacsuk,et al.  P‐GRADE portal family for grid infrastructures , 2011, Concurr. Comput. Pract. Exp..

[3]  Robert Allan Virtual research environments : from portals to science gateways , 2009 .

[4]  S. V. Smirnov,et al.  Implementation of Concurrent Parallelization of Branch-and-bound algorithm in Everest Distributed Environment , 2017 .

[5]  Zhao Zhang,et al.  Toward loosely coupled programming on petascale systems , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.

[6]  Oleg Sukhoroslov,et al.  A Web-Based Platform for Publication and Distributed Execution of Computing Applications , 2015, 2015 14th International Symposium on Parallel and Distributed Computing.

[7]  Michael McLennan,et al.  HUBzero: A Platform for Dissemination and Collaboration in Computational Science and Engineering , 2010, Computing in Science & Engineering.

[8]  Anton Nekrutenko,et al.  Galaxy: A Gateway to Tools in e-Science , 2011, Guide to e-Science.

[9]  Oleg Sukhoroslov,et al.  A Generic Web Service for Running Parameter Sweep Experiments in Distributed Computing Environment , 2015 .

[10]  Ambros M. Gleixner,et al.  SCIP: global optimization of mixed-integer nonlinear programs in a branch-and-cut framework , 2018, Optim. Methods Softw..

[11]  Kurt Maly,et al.  Web-based Framework for Distributed Computing , 1997, Concurr. Pract. Exp..

[12]  Oleg Sukhoroslov,et al.  Integration and Combined Use of Distributed Computing Resources with Everest , 2016 .

[13]  A R Formiconi,et al.  World Wide Web interface for advanced SPECT reconstruction algorithms implemented on a remote massively parallel computer. , 1997, International journal of medical informatics.

[14]  Jay Boisseau,et al.  Development of Web toolkits for computational science portals: the NPACI HotPage , 2000, Proceedings the Ninth International Symposium on High-Performance Distributed Computing.

[15]  Xiaoyu Yang,et al.  Survey of major tools and technologies for grid-enabled portal development. , 2006 .

[16]  Oleg R. Musin,et al.  The Tammes Problem for N = 14 , 2014, Exp. Math..

[17]  Oleg Sukhoroslov,et al.  Implementation and Use of Coarse-grained Parallel Branch-and-bound in Everest Distributed Environment , 2017, ICCS.

[18]  Geoffrey C. Fox,et al.  Grid portal architectures for scientific applications , 2005 .

[19]  Ian Foster,et al.  The Grid 2 - Blueprint for a New Computing Infrastructure, Second Edition , 1998, The Grid 2, 2nd Edition.

[20]  Geoffrey C. Fox,et al.  The Gateway computational Web portal , 2002, Concurr. Comput. Pract. Exp..

[21]  Benjamin Müller,et al.  The SCIP Optimization Suite 5.0 , 2017, 2112.08872.

[22]  Oleg Sukhoroslov,et al.  Simplifying the Use of Clouds for Scientific Computing with Everest , 2017 .

[23]  Oleg Sukhoroslov,et al.  MathCloud: Publication and Reuse of Scientific Applications as RESTful Web Services , 2013, PaCT.