Re: [JINST] JINST_056P_0721 - your minor revision

[David Carl Sagan]

FYI: The paper will be submitted early next week.

— Cheers, David

> On Aug 20, 2021, at 4:55 AM, JINST Editorial Office <jins...@jinst.sissa.it> wrote:
>
> Preprint: JINST_056P_0721
> Title : Simulations of Future Particle Accelerators: Issues and Mitigations
> Authors : D. Sagan et. al.
>
>
> Dear Prof. David Sagan,
>
> we would like to remind you that authors are kindly requested to submit their minor revisions
> in no more than 2 weeks -24 August 2021 in your case.
> We hope that you will be able to meet this deadline.
>
> For your information, deadline extensions can be requested, if necessary,
> using the button "write to Editorial Office" on the author pages.
> In case the deadline expires and authors fail to request an extension, the preprint is withdrawn
> from the journal.
>
>
> Thank you and best wishes,
> JINST Editorial Office
>
>
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[Georg Heinz Hoffstaetter]

Hi David,

thanks for leading this through publication!

Georg

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[David Carl Sagan]

Hi All:

Attached is latest draft of the paper. Submission will be in about 24 hours. Last minute corrections are always welcome.

                                        — Cheers, David

[David Carl Sagan]

Hi All:

The question was asked if there are references that could be used with the following paragraph in the paper:

Beyond the data exchange through common file formats and meta-data schemata, it is sometimes desirable to exchange data among the simulation tools in a more integrated, finer-grained manner (for example, for each simulation time step). This may happen when multiple physics effects are to be simultaneously simulated or when coupling multiple solvers, where data exchange can be either in single direction or bi-directional. Such an in-memory or cross-node data transfer can be made to respect physics constraints (conservation, divergence free conditions, etc.) and is also much more efficient than file I/O based transfers. This need can be best served with the common low-level data layouts and interfaces as mentioned above and/or by promoting/enabling interoperable mesh/particle capabilities among existing tools in the ecosystem.  

If anyone has anything please come forward.

— Thanks, David

<ICFA_Accelerator_Simulation.pdf><ICFA_Accelerator_Simulation.zip>

[Nathan Cook]

Hi David,

I did not write this paragraph, so I will gladly defer to the author(s) preferences. However, in-memory data transfer and interfacing is indicative of an in-situ computing paradigm, and I suggest following references for this specific type of application.

1. F. Zhang, et al., "In-memory staging and data-centric task placement for coupled scientific simulation workflows," Concurrency Computat: Pract Exper. 2017. 29:e4147. https://doi.org/10.1002/cpe.4147
2. U. Ayachit et al., "Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures," SC '16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 2016. pp. 921-932, https://doi.org/10.1109/SC.2016.78
   
3. M. Larsen et al., "The ALPINE In Situ Infrastructure: Ascending from the Ashes of Strawman," Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization (ISAV'17). 2017. pp. 42–46. https://doi.org/10.1145/3144769.3144778 
   

Best,

Nathan

[Huang, Chengkun]

Hi David,

I wrote this part and was thinking the following scenarios for motivation:

1. Coupled simulations of high brightness RF guns with detailed solid-state physics models of photocathode materials, e.g.

         https://accelconf.web.cern.ch/p05/PAPERS/TPPE039.PDF,

         as well as the snowmass LOI I have written (https://www.snowmass21.org/docs/files/summaries/AF/SNOWMASS21-AF7_AF1-CompF2_CompF0_Huang-183.pdf, already in references)

 

     2. CSR modeling with quasi-realistic vacuum chamber where Green's function based solver (most current CSR solvers are of this type) can be coupled to other RF cavity solvers.

        such need is pointed out in one of the work group paper, https://arxiv.org/ftp/arxiv/papers/2101/2101.04107.pdf

There may be other needs that can motivate the such data transfer and interfacing, but Nathan's suggestions on the general trend in in-situ computing are also very good.

Thanks,

Chengkun

---

From: Nathan Cook <nc...@radiasoft.net>
Sent: Tuesday, August 24, 2021 11:49 AM
To: David Carl Sagan
Cc: AccBeamModelSnowmass21
Subject: [EXTERNAL] Re: [AccBeamModelSnowmass21] Re: JINST_056P_0721 Penultimate Draft

 

[David Carl Sagan]

OK I have added these.

— Thanks, David

[David Carl Sagan]

OK I have added these references. Attached is the latest version of the paper

— Best, David

On Aug 24, 2021, at 2:20 PM, Huang, Chengkun <hua...@lanl.gov> wrote:

Hi David,

I wrote this part and was thinking the following scenarios for motivation:

1. Coupled simulations of high brightness RF guns with detailed solid-state physics models of photocathode materials, e.g.

         https://accelconf.web.cern.ch/p05/PAPERS/TPPE039.PDF,

         as well as the snowmass LOI I have written (https://www.snowmass21.org/docs/files/summaries/AF/SNOWMASS21-AF7_AF1-CompF2_CompF0_Huang-183.pdf, already in references)

  

     2. CSR modeling with quasi-realistic vacuum chamber where Green's function based solver (most current CSR solvers are of this type) can be coupled to other RF cavity solvers.

        such need is pointed out in one of the work group paper, https://arxiv.org/ftp/arxiv/papers/2101/2101.04107.pdf

There may be other needs that can motivate the such data transfer and interfacing, but Nathan's suggestions on the general trend in in-situ computing are also very good. 

Thanks,

Chengkun

---

From: Nathan Cook <nc...@radiasoft.net>
Sent: Tuesday, August 24, 2021 11:49 AM
To: David Carl Sagan
Cc: AccBeamModelSnowmass21
Subject: [EXTERNAL] Re: [AccBeamModelSnowmass21] Re: JINST_056P_0721 Penultimate Draft

 

Hi David,

I did not write this paragraph, so I will gladly defer to the author(s) preferences. However, in-memory data transfer and interfacing is indicative of an in-situ computing paradigm, and I suggest following references for this specific type of application.

1. F. Zhang, et al., "In-memory staging and data-centric task placement for coupled scientific simulation workflows," Concurrency Computat: Pract Exper. 2017. 29:e4147. https://doi.org/10.1002/cpe.4147

1. U. Ayachit et al., "Performance Analysis, Design Considerations, and Applications of Extreme-Scale In Situ Infrastructures," SC '16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 2016. pp. 921-932,https://doi.org/10.1109/SC.2016.78
   

Best,

Nathan

[Axel Huebl]

Great refs, I second those - sorry, my day was too full to respond in the given time frame.

--

Axel Huebl

Computational Physicist, Research Software Engineer

Accelerator Technology and Applied Physics Division

Lawrence Berkeley National Laboratory

Berkeley, CA

Pronouns: he/him/his