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Automating NEURON Simulation Deployment in Cloud Resources

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Abstract

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the OpenStack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon’s proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model.

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Notes

  1. https://www.openstack.org/user-stories/cern/

  2. CQSCS = Construction Quality Supervision Collaboration System.

  3. https://www.chameleoncloud.org/about/hardware-description/

  4. https://www.chameleoncloud.org/docs/bare-metal-user-guide/

  5. KVM = Kernel-based Virtual Machine and refers to the type of hypervisor employed by the cloud to run virtual machines; see http://www.linux-kvm.org.

  6. https://aws.amazon.com/free/

  7. These details can be seen at https://aws.amazon.com/ec2/instance-types/ https://aws.amazon.com/ec2/instance-types/.

  8. https://aws.amazon.com/ec2/purchasing-options/dedicated-instances/

  9. Discussion here: https://www.rackspace.com/cloud/public-pricing#cloud-servers and calculator here: https://www.rackspace.com/calculator

  10. Discussion here: https://aws.amazon.com/ec2/pricing/ and calculator here: http://calculator.s3.amazonaws.com/index.html

  11. https://aws.amazon.com/ec2/purchasing-options/

  12. In NEURON, mod files are used to define the simulation program for a biomechanism such as an ion channel. After definition, they are translated into C code and compiled into a biomechanism library before use in actual simulation.

  13. http://www.openstack.org

  14. AMI = ‘Amazon Machine Image’.

  15. http://www.neuron.yale.edu/neuron/download/compile_linux

  16. http://www.davison.webfactional.com/notes/installation-neuron-python/

  17. Available free at http://www.mathworks.com/products/compiler/mcr/; the version matches the MATLAB compiler we have available.

  18. https://github.com/SantamariaLab/NeuroManager

  19. https://www.chameleoncloud.org/appliances/

  20. ‘JSON’ stands for Javascript Object Notation. Please see http://www.json.org/.

  21. http://docs.openstack.org/user-guide/common/cli_overview.html

  22. https://aws.amazon.com/cli

  23. http://www.drdobbs.com/web-development/restful-web-services-a-tutorial/240169069

  24. http://developer.openstack.org/api-ref.html

  25. See RFCs 7230–7237 at http://tools.ietf.org/rfc/index

  26. http://developer.openstack.org/api-guide/quick-start/api-quick-start.html

  27. http://docs.aws.amazon.com/AWSEC2/latest/APIReference/making-api-requests.html

  28. https://wiki.openstack.org/wiki/SDKs

  29. http://docs.openstack.org/developer/python-novaclient/ref/v2/serverser.html

  30. https://curl.haxx.se/

  31. 31 See, for example, the Java SDK: https://aws.amazon.com/sdk-for-java/.

  32. The JSON format is similar to the XML format but much less cluttered. It permits hierarchical data definition, whereas the more familiar INI files do not.

  33. OpenStack API: http://developer.openstack.org/api-guide/quick-start/ http://developer.openstack.org/api-guide/quick-start/

  34. Rackspace API: https://developer.rackspace.com/docs/cloud-servers/v2/developer-guide/#api-reference https://developer.rackspace.com/docs/cloud-servers/v2/developer-guide/#api-reference

  35. By programming the UserSimulation() function accordingly; see Stockton and Santamaria (2015).

  36. Cloud clusters are virtual networks formed from cloud instances.

  37. The hypervisor is the program that runs on the physical processor and produces the virtual machines, or cloud servers, that are hosted by the physical processor.

  38. The approach is also suitable for multi–node cluster–based simulations but we focus on single–node applications here.

  39. Note that cluster and cloud nodes are often limited in cores to eight or fewer each.

  40. Model 17664; see https://senselab.med.yale.edu/modeldb/ShowModel.cshtml?model=17664.

  41. 41 See https://github.com/SantamariaLab/NeuroManager/tree/master/NeurSim/MiyashoMOD/KhStudy.

  42. http://cbi.utsa.edu/hardware/cluster

  43. Except for Amazon; there is a licensing fee for Centos–7 usage on Amazon EC2, and it must be obtained through the AWS Marketplace. See https://aws.amazon.com/marketplace/b/2649367011.

  44. Our experiments did not make use of server migration or load balancing of any kind, however NeuroManager’s scheduler favors faster Simulators.

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Acknowledgments

NSF-EF1137897, NSF-DBI1451032, NIH-G12MD007591 (for use of computational facilities at UTSA), Texas Advanced Computing Center for providing HPC resources, and the Computational System Biology Core at UTSA for providing access to the Chameleon Cloud facilities.

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Authors and Affiliations

  1. Department of Biomedical Engineering, The University of Texas at San Antonio, San Antonio, TX, 78249, USA

    David B. Stockton

  2. Department of Biology, The University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Fidel Santamaria

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  1. David B. Stockton
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  2. Fidel Santamaria
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Correspondence to David B. Stockton.

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Conflict of interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

We made use of Rackspace’s developer program (Rackspace 2016b) which provides $50 free access per month to any developer for one year; we paid for all use above that amount. We also made use of Amazon’s Free Tier (https://aws.amazon.com/free/) which gives any developer free access to 750 hours per month of instances built upon the “t2.micro” flavor for one year; we paid for all use above that amount as well as use of all flavors that were not “t2.micro”.

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Information Sharing Statement

The NeuroManager software and instance configuration scripts are available at https://github.com/SantamariaLab/NeuroManagerunder an open source license that is presented at that location. MATLAB commercial software is available at http://www.mathworks.com/products/matlab/. Other software mentioned in this paper is freely available and has a footnote indicating the URL at which it can be found. The Miyasho model used in all simulations is available at ModelDB (RRID:SCR_007271, Model 17664).

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Stockton, D.B., Santamaria, F. Automating NEURON Simulation Deployment in Cloud Resources. Neuroinform 15, 51–70 (2017). https://doi.org/10.1007/s12021-016-9315-8

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