# Monte Carlo production tools ## Monte Carlo production tools - [Introduction](https://cms-pdmv.gitbook.io/project/readme.md): This document aims to join useful technical information for MC contacts and MC requests managers working in PdmV - [Monte Carlo production overview](https://cms-pdmv.gitbook.io/project/monte-carlo-production-overview.md): In this page, we describe the general idea of central Monte Carlo production. - [Monte Carlo Management (McM): introduction](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-introduction.md): In this page, we describe the general ideas and steps of the central Monte Carlo production - [Analyzer's corner](https://cms-pdmv.gitbook.io/project/analyzers-corner.md): In this page, we give a basic explanation of the glossary, needed for analysers to understand the logic of the central MC production - [Monitoring submitted requests](https://cms-pdmv.gitbook.io/project/analyzers-corner/untitled-3.md) - [How to search for datasets in DAS and McM](https://cms-pdmv.gitbook.io/project/analyzers-corner/how-to-search-for-datasets-in-mcm.md) - [How to find the fragment of a request in McM](https://cms-pdmv.gitbook.io/project/analyzers-corner/how-to-find-the-fragment-of-a-request-in-mcm.md) - [How to find the cmsDriver used for a certain request](https://cms-pdmv.gitbook.io/project/analyzers-corner/how-to-find-the-cmsdriver-used-for-a-certain-campaign.md) - [How to use randomized parameters samples](https://cms-pdmv.gitbook.io/project/analyzers-corner/how-to-use-randomized-parameters-samples.md): Randomized parameters is a sample generation method in which a whole signal grid is generated in a single dataset. This page documents the use of such samples for analyzers. - [Monte Carlo contact's corner](https://cms-pdmv.gitbook.io/project/mccontact.md): In this page, we collect useful information for Monte Carlo contacts about how to act in McM - [Rules for dataset names](https://cms-pdmv.gitbook.io/project/mccontact/rules-for-dataset-names.md): In this page, we list some rules which should be used for choosing the name of a dataset in McM - [Rules for Run3 dataset names](https://cms-pdmv.gitbook.io/project/mccontact/rules-for-run3-dataset-names.md) - [Rules for Run3 2024 dataset names](https://cms-pdmv.gitbook.io/project/mccontact/rules-for-run3-2024-dataset-names.md) - [How to create a new ticket](https://cms-pdmv.gitbook.io/project/mccontact/how-to-create-a-new-ticket.md) - [High priority requests](https://cms-pdmv.gitbook.io/project/mccontact/high-priority-requests.md) - [Scripting in McM](https://cms-pdmv.gitbook.io/project/mccontact/scripting-in-mcm.md): In this page, some examples of scripts which can be used in McM for queries and actions are listed. - [Request checking script](https://cms-pdmv.gitbook.io/project/mccontact/request-checking-script.md): This page describes the usage of monte carlo request checking script in CMS that uses McM info and gridpacks and does automated patches for certain type of problem in MG5\_aMC in the CMSSW setup. - [News and current request policy](https://cms-pdmv.gitbook.io/project/mccontact/news-and-current-request-policy.md): This page tries to keep track of updated information about chains, campaigns and priority blocks currently used in production. - [Interactive MC contact exercises](https://cms-pdmv.gitbook.io/project/mccontact/interactive-mc-contact-exercises.md) - [Randomized Parameters](https://cms-pdmv.gitbook.io/project/mccontact/signal-mass-points-in-single-ticket.md): This will describe how to generalize the fragmentation. - [Info for MC production for Ultra Legacy Campaigns 2016, 2017, 2018](https://cms-pdmv.gitbook.io/project/mccontact/info-for-mc-production-for-ultra-legacy-campaigns-2016-2017-2018.md) - [Info for MC production for Run3 Campaigns](https://cms-pdmv.gitbook.io/project/mccontact/info-for-mc-production-for-run3-campaigns.md) - [Request manager's corner](https://cms-pdmv.gitbook.io/project/reqmgr.md): In this page, we collect the relevant information for request managers - [\[DRAFT\] MultiValidation in McM](https://cms-pdmv.gitbook.io/project/reqmgr/draft-multivalidation-in-mcm.md): Multiple step request validation in McM - [Procedure how to create and setup a campaign](https://cms-pdmv.gitbook.io/project/reqmgr/procedure-how-to-create-and-setup-a-campaign.md): Very important for a request manager is to open campaigns where to submit requests. In this page. - [Fast Simulation Campaigns](https://cms-pdmv.gitbook.io/project/reqmgr/fast-simulation-campaigns.md): This is to talk about the SUSY FastSim campaign that is used for signal samples. - ["Dead" requests and tickets](https://cms-pdmv.gitbook.io/project/reqmgr/dead-requests-and-tickets.md) - [Computing's corner](https://cms-pdmv.gitbook.io/project/computing.md): In this page, more advanced information about status of requests in computing is collected. - [Status of requests in computing](https://cms-pdmv.gitbook.io/project/computing/untitled-2.md): In this page, we collect useful information for Monte Carlo contacts about how to act in McM - [Errors in production: explanation](https://cms-pdmv.gitbook.io/project/computing/errors-in-production-explanation.md): In this section, we comment on the errors observed in production and on the possible solutions that should be adopted to correct them. (page to be completed) - [Task chain vs step chain](https://cms-pdmv.gitbook.io/project/computing/task-chain-vs-step-chain.md): From Alan Malta Rodrigues' wiki page: https://github.com/dmwm/WMCore/wiki/TaskChain-vs-StepChain - [cmsDriver argument and meaning](https://cms-pdmv.gitbook.io/project/cmsdriver-argument-and-meaning.md): This page gives an overview of the most important use cases of the cmsDriver command - [runTheMatrix and release validation](https://cms-pdmv.gitbook.io/project/cmsdriver-argument-and-meaning/runthematrix-and-release-validation.md) - [Monte Carlo Management (McM): detailed guide](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-detailed-guide.md) - [McM Glossary: requests](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-detailed-guide/mcm-glossary.md): In this page, we give a description of icons and features of requests in McM - [McM glossary: chained requests](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-detailed-guide/mcm-glossary-chained-requests.md): In this page, we give a description of icons and features of chained requests in McM - [McM glossary: campaigns](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-detailed-guide/mcm-glossary-campaigns.md): In this page, we give a description of icons and features of campaigns in McM - [McM glossary: flows](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-detailed-guide/mcm-glossary-flows.md): In this page, we give a description of icons and features of flows in McM - [McM glossary: tickets](https://cms-pdmv.gitbook.io/project/monte-carlo-management-mcm-detailed-guide/mcm-glossary-tickets.md): In this page, we give a description of icons and features of tickets in McM - [Production Monitoring Platform (pMp): detailed guide](https://cms-pdmv.gitbook.io/project/production-monitoring-platform-pmp-introduction.md) - [Data reprocessing (old injection method via script)](https://cms-pdmv.gitbook.io/project/data-reprocessing.md): This page aims for explaining how to perform data reprocessing from the available tools in cmssw. Adapted from twiki page by Francesco Fabozzi. - [FAQ](https://cms-pdmv.gitbook.io/project/untitled-4.md): This is a developing page, which contains some of the frequently asked questions. - [Contacts](https://cms-pdmv.gitbook.io/project/contacts.md): In this page, we collect the contacts of the responsible people for this manual. - [Group Analysis Samples Page: GrASP](https://cms-pdmv.gitbook.io/project/group-analysis-samples-page-grasp.md): Production monitoring tool called Group Analysis Samples Page - [Tagging on GrASP](https://cms-pdmv.gitbook.io/project/group-analysis-samples-page-grasp/tagging-on-grasp.md): How to tag and follow a group of samples on GrASP --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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