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Article
Peer-Review Record

An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-Based Energy Infrastructure Resilience Studies

Computation 2023, 11(12), 243; https://doi.org/10.3390/computation11120243
by Alexander Feoktistov 1,*, Alexei Edelev 2, Andrei Tchernykh 3,4, Sergey Gorsky 1, Olga Basharina 1,5 and Evgeniy Fereferov 1
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Computation 2023, 11(12), 243; https://doi.org/10.3390/computation11120243
Submission received: 30 October 2023 / Revised: 19 November 2023 / Accepted: 21 November 2023 / Published: 4 December 2023

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I read whole this paper and it can be published after some minor modification that I mention as follows:

 

1- figs should be improved

2- Authors should take help from English speakers because there are a lot of grammar errors found. 

3- Can you improve conclusion and abstract?

 

Comments on the Quality of English Language

Needs improve

Author Response

Dear Reviewer,

Thank you for taking your time to review our paper. We appreciate your valuable suggestions for improving the paper. Following your suggestions, we have carefully revised the paper. Below is a summary of the changes we have made to the paper. Our response is typed after reviewer’s comments.

Reviewer’s report

I read whole this paper and it can be published after some minor modification that I mention as follows:

#1- figs should be improved

– Done. We have improved the quality of all figures.

#2 - Authors should take help from English speakers because there are a lot of grammar errors found.

– Done. We have performed the required spelling check.

#3 - Can you improve conclusion and abstract?

– Done. We have clarified the objectives and results of the study to improve the abstract and conclusions.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The authors present a complete workflow to evaluate the vulnerability of a power grid, using In-Memory Database and HPC clusters. The paper is generally easy to read, although some details of the application itself (e.g. what resources are modeled and to what level of details, how grid power is computed).

I also get the impression that the Global Vulnerability Analysis application is embarrassingly parallel (each scenario can be computed independently of others), so I am not too surprised that linear scalability is obtained; but I may have misunderstood.

 

Comments on the Quality of English Language

Generally, the document is easy to read. A few nodes though:

* l.82: natural-climatic -> natural, climatic ?

* l.84 : Analysing the dependence... because of... -> Formulation is not very clear

* l.91 : missing 'is' before 'the vulnerability' ?

* l92: Perahps add "for Configurations 1, 2 and 3, respectively  ? 

Author Response

Dear Reviewer,

Thank you for reviewing our paper and providing helpful comments. We appreciate it. According to your comments, we have carefully corrected the paper. Our response is typed after reviewer’s comments.

Reviewer’s report

The authors present a complete workflow to evaluate the vulnerability of a power grid, using In-Memory Database and HPC clusters. The paper is generally easy to read, although some details of the application itself (e.g. what resources are modeled and to what level of details, how grid power is computed).

I also get the impression that the Global Vulnerability Analysis application is embarrassingly parallel (each scenario can be computed independently of others), so I am not too surprised that linear scalability is obtained; but I may have misunderstood.

– Thanks for the comment! We achieve near-linear speedup in each resource due to parallel processing of disturbance scenarios and rational distribution of the computational load for processing series of scenarios on the different resources. We have added this clarification to the conclusions.

Generally, the document is easy to read. A few nodes though:

– Thank you for your careful consideration of our paper and helpful corrections. Below are the changes made to the paper based on your comments below.

* l.82: natural-climatic -> natural, climatic ?

– Done. We have corrected the text according to your suggestion.

* l.84 : Analysing the dependence... because of... -> Formulation is not very clear

– Done. We have clarified the meaning of the sentence as follows: “We can compare different energy infrastructure configurations in terms of vulnerability based on analyzing the performance degradation that is due to a disturbance.”

* l.91 : missing 'is' before 'the vulnerability' ?

– Done. We have corrected the text as follows: “The metrics , , and  equal  show the vulnerability …”

* l.92: Perahps add "for Configurations 1, 2 and 3, respectively  ?

– Done. We have expanded the text according to your suggestion as follows: “… due to the performance degradation in the two states above for Configurations 1, 2, and 3, respectively.”

Best regards,

Alexander Feoktistov

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The paper ‘An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-based Energy Infrastructure Resilience Studies’ is an interesting paper, important both from a political-economic-social point of view and from the point of view of the "technology" that it proposes to use to study the resilience of energy infrastructures.

Studying energy infrastructure resilience, in fact, is essential for safeguarding the functionality, security, and sustainability of energy systems. It involves a proactive approach to identifying vulnerabilities, mitigating risks, and ensuring a reliable and resilient energy supply for the benefit of societies and economies.

More strictly from the point of view of computer science/computational engineering, the paper offers a sufficiently original implementation of a combined set of tools and concepts, High Performance Computing, Distributed Databases, Workflows, ... and so on.

The reviewer’ opinion is that the paper could be accepted with a minor revision. Just a consideration. The authors discuss about their approach (a mixed parallel, grid, cloud computing), and they implement it … on a cluster! Could the authors, then, better clarify, highlight, underline, for example, where and how the grid and/or cloud computing is tested?

Author Response

Dear Reviewer,

Thank you for your detailed consideration of our study and acceptance of our paper. We appreciate it. Our response is typed after reviewer’s comments.

Reviewer’s report

The paper ‘An Approach to Implementing High-Performance Computing for Problem Solving in Workflow-based Energy Infrastructure Resilience Studies’ is an interesting paper, important both from a political-economic-social point of view and from the point of view of the "technology" that it proposes to use to study the resilience of energy infrastructures.

Studying energy infrastructure resilience, in fact, is essential for safeguarding the functionality, security, and sustainability of energy systems. It involves a proactive approach to identifying vulnerabilities, mitigating risks, and ensuring a reliable and resilient energy supply for the benefit of societies and economies.

More strictly from the point of view of computer science/computational engineering, the paper offers a sufficiently original implementation of a combined set of tools and concepts, High Performance Computing, Distributed Databases, Workflows, ... and so on.

The reviewer’ opinion is that the paper could be accepted with a minor revision. Just a consideration. The authors discuss about their approach (a mixed parallel, grid, cloud computing), and they implement it … on a cluster! Could the authors, then, better clarify, highlight, underline, for example, where and how the grid and/or cloud computing is tested?

– Thanks for the comment! The HPC clusters used for the experiments are geographically distributed and have different administrative affiliations. Therefore, we consider our experimental computing environment consisting of resources from these clusters as a computational Grid. We have included this clarification in Section 5 after the description of HPC Clasters 1, 2, and 3. In the future, we plan to conduct more large-scale experiments using additional cloud resources.

Best regards,

Alexander Feoktistov

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

All my comments have been done so I recommend this paper to accept. 

Comments on the Quality of English Language

it is ok

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