Using Resources of Supercomputing Centers with Everest Platform

Smirnov, Sergey A.; Sukhoroslov, Oleg V.; Voloshinov, Vladimir V.

doi:10.1007/978-3-030-05807-4_59

Cited by 4 publications

(4 citation statements)

References 18 publications

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“…The process of integrating ParaSCIP solver into DDBNB is different from the integration of the previously added CBC and SCIP [1,2,3] solvers. ParaSCIP is a parallel application that runs on a computing cluster and uses MPI (Message Passing Interface) to exchange data between solver processes and a Load Coordinator process [fig.…”

Section: Ug/parascip Ddbnb and Everest Modificationmentioning

confidence: 99%

“…To run DDBNB with ParaSCIP, a separate Everest agent was configured on the clusters using the basic "local" computing resource adapter, which allows to fork processes on the cluster's submission node. We did not use specialized adapter with SLURM support [2] which allows running on a cluster only batches of jobs with one process each, because with ParaSCIP it is necessary to request the cluster's resource manager to allocate resources with several processes within one job.…”

Section: Computational Experimentsmentioning

confidence: 99%

“…DDBNB [1,2,3] is a distributed application processing a set of computational tasks in parallel . Each of T is a pair {P, S}, where P is the initial data of some mathematical programming problem (represented as NL-file), S is a set of solver settings.…”

Section: Introductionmentioning

confidence: 99%

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Concurrently Employing Resources of Several Supercomputers With Parascip Solver by Everest Platform

Smirnov¹,

Voloshinov²,

Sukhoroslov³

2021

9th International Conference "Distributed Computing and Grid Technologies in Science and Education"

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ParaSCIP is rather advanced open-source solver for discrete and global optimization problems. Thissolver is distinguished by that it can run on distributed memory systems and use up to 80,000 cores,solving open problems from the MIPLIB test libraries. Earlier, using this solver, we confirmed theconjecture on optimal packing of nine congruent circles on a square flat torus. The goal of the studywas to increase computing performance by utilizing resources of multiple clusters to solve hardoptimization problem. To do this, we use the previously developed DDBNB application, which allowsto speed up the solution of optimization problems by using coarse-grained parallelization based on astatic decomposition of feasible domain made before solving starts. DDBNB is an application for theEverest distributed computing platform which is responsible for running jobs on heterogeneouscomputing resources (servers, cloud instances, clusters, etc.). As a result, DDBNB, Everest, andParaSCIP had to be modified to make it possible to exchange incumbents (feasible solutions found bythe solver) between several ParaSCIP instances running on different supercomputers. The resultingsystem was benchmarked using three different instances of Traveling Salesman Problem. Thesupercomputers HPC5 of the NRC “Kurchatov Institute” and cHARISMa of the HSE University wereused as computing resources. As a result, for two problem instances, there is an effect, and thespeedup is especially noticeable for a more complex problem. However, for a simpler problem, theexchange of incumbents does not seem to affect the amount of speedup. For the third instance, there isno particular effect, at least no slowdown is observed.

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Section: Ug/parascip Ddbnb and Everest Modificationmentioning

confidence: 99%

Section: Computational Experimentsmentioning

confidence: 99%

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Concurrently Employing Resources of Several Supercomputers With Parascip Solver by Everest Platform

Smirnov¹,

Voloshinov²,

Sukhoroslov³

2021

9th International Conference "Distributed Computing and Grid Technologies in Science and Education"

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show abstract

“…This designation typically refers to the use of aggregated computing power to solve advanced computational problems related to scientific research [2]. Most of these services are composed of cluster-based supercomputers and are important for providing the computational resources and applications necessary in various scientific fields [3]. These supercomputing services are often divided into highperformance computing (HPC) services and high-throughput computing (HTC) services [4] according to the workflow of the job.…”

Section: Introductionmentioning

confidence: 99%

HPC Cloud Architecture to Reduce HPC Workflow Complexity in Containerized Environments

Woo

Lim

2021

Applied Sciences

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The complexity of high-performance computing (HPC) workflows is an important issue in the provision of HPC cloud services in most national supercomputing centers. This complexity problem is especially critical because it affects HPC resource scalability, management efficiency, and convenience of use. To solve this problem, while exploiting the advantage of bare-metal-level high performance, container-based cloud solutions have been developed. However, various problems still exist, such as an isolated environment between HPC and the cloud, security issues, and workload management issues. We propose an architecture that reduces this complexity by using Docker and Singularity, which are the container platforms most often used in the HPC cloud field. This HPC cloud architecture integrates both image management and job management, which are the two main elements of HPC cloud workflows. To evaluate the serviceability and performance of the proposed architecture, we developed and implemented a platform in an HPC cluster experiment. Experimental results indicated that the proposed HPC cloud architecture can reduce complexity to provide supercomputing resource scalability, high performance, user convenience, various HPC applications, and management efficiency.

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Optimal Packings of Congruent Circles on a Square Flat Torus as Mixed-Integer Nonlinear Optimization Problem

Voloshinov

Smirnov

2019

Communications in Computer and Information Science

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Using Resources of Supercomputing Centers with Everest Platform

Cited by 4 publications

References 18 publications

Concurrently Employing Resources of Several Supercomputers With Parascip Solver by Everest Platform

Concurrently Employing Resources of Several Supercomputers With Parascip Solver by Everest Platform

HPC Cloud Architecture to Reduce HPC Workflow Complexity in Containerized Environments

Optimal Packings of Congruent Circles on a Square Flat Torus as Mixed-Integer Nonlinear Optimization Problem

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