Sensitivity of Mitigation Scenarios to Societal Choices
Modeling studies explore future energy systems using the Integrated Assessment Model MESSAGEix-GLOBIOM to quantify key variables for long-term analysis. The project aims to run sequentially on virtual machines provided by EOSC, utilizing services for job processing and distributed storage.
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Presentation Transcript
Mapping the sensitivity of mitigation scenarios to societal choices IIASA: Bas van Ruijven, Paul Kishimoto, Nikolay Kushin EOSC: Alessandro Costantini GTM-P1 Early Adopter Programme monthly call, 20-02-2020
Brief description of project Perform modeling studies to explore future energy systems Integrated Assessment Model MESSAGEix-GLOBIOM Integrated energy, environment, and economic systems Quantify key variables for long-term future Proof-of-principle platform aimed at performing large scale (10-15k model runs) analyses.
Use Case MESSAGEix-GLOBIOM will run sequentially on the selected resources, each job is independent from the other in a parametric fashion. The model will run in Virtual Machines provided by EOSC. Submitted by batch system, manually deployed by the applicants. Exploratory runs of software stack in a containerized environment (using docker) on larger compute systems (e.g., HTC) (TRL5 -> TRL9) A Mesos/Marathon cluster can be instantiated on the provided cloud resources and the parametrized simulations can run in it as independent containers. The output carried out from the simulations will be stored in a distributed environment where can be accessed from different locations for post-processing analysis. 3
Services and resources EOSC Federated Authentication mechanism 1. EGI Cloud Compute service Services to access virtual machines, containers and job processing to support general computing needs. 200 vCPUs cores, 800GB of RAM and 6TB of distributed storage. The project is not experienced to use Cloud or EOSC resources and services in general. 2. Storage service Distributed storage will enable collection of the results and the analysis of the outcomes. Takes the form of a managed database service (e.g. PostgreSQL) 3. 4
Time planning Q1: Infrastructure resource provisioning and settings Enable federated identity management using one of the available AAI solutions provided by EOSC-hub. Finalize and test containerized runs Q2: Feasibility study on the integration between the AAI solutions provided by EOSC-hub and the community specific AuthN/AuthZ mechanism Set up the IAM platform and perform initial tests for model run. 5
Time planning Q3: Tune the platform services (Compute, Data Management) Increase the scale of the tests of the platform in EOSC. Analysis of results Q4: Analysis of results Registration of the IAM Platform in the EOSC Portal to be adopted by the community. Investigate and verify the sustainability of the Platform for production purposes. 6
Current status Getting access to EOSC resources Preparing components for cloud deployment 7
Thank you very much for your attention! Dr. Bas van Ruijven Senior Research Scholar Energy Program International Institute for Applied Systems Analysis (IIASA) Laxenburg, Austria vruijven@iiasa.ac.at www.iiasa.ac.at This presentation is licensed under Creative Commons Attribution 4.0 International License a Creative Commons Attribution 4.0 International License
