October 2013 - Allocations-admins - mailman3.cels.anl.gov

Re: [allocations-admins] [LCRC Accounts] Project Request: VERITAS
by Bair, Raymond A. 04 Oct '13

04 Oct '13

Yes, that looks good. Ray ----------------------------------------- Ray Bair Computing, Environment, and Life Sciences Argonne National Laboratory and the University of Chicago TCS Building 240, Room 4122 9700 South Cass Avenue Argonne, IL 60439 email: rbair(at)anl.gov Phone: (630)252-5751 On 10/3/13 9:13 PM, "John Valdes" <valdes(a)anl.gov> wrote: >Forgot that this new project came in on Tue. OK to approve the full >200K for the full FY? One concern is that the PI says analysis will >involve a "few TB of disk" which we currently don't have (but will >soon). My take on the metadata (please correct): > > PoC: Steve Pieper > Pri: 3 > Cat: P > Sub: Phy > >John > >On Tue, Oct 01, 2013 at 03:11:50PM -0500, accounts(a)lcrc.anl.gov wrote: >> Hello, >> >> A new project on the LCRC cluster has been requested. Please forward >> the information on to the LCRC Allocation sub-committee. >> >> Applicant's name: Benjamin Zitzer >> Applicant's institution: ANL >> Applicant's division: HEP >> Project Name: VERITAS >> Project title: KASCADE Simulations for VERITAS >> Associated funding: DOE >> Other Systems: NERSC at Berkley, 400,000 hours plus an >>200,000 extension >> Hansen at Purdue University, 400,000 hours (not allocated) >> Science: VERITAS, the Very Energetic Radiation Imaging >>Telescope Array >> System, located in Southern Arizona at the Whipple Observatory Base >>camp, is an array of imaging atmospheric Cherenkov telescopes designed >>to detect very-high-energy (VHE) >> gamma rays (85 GeV - 50 TeV) that shower in the earth's atmosphere. VHE >>energy spectra of active galaxies, pulsars, and the associated pulsar >>wind nebulae are now able >> in many cases to constrain models of the acceleration mechanisms >>responsible for the photon production. Constraints are usually even >>stronger when we perform a simultaneous >> multi-wavelength analysis by combining VERITAS spectra with other >>spectra from partner observatories. >> The results of our work are distributed through releases of the VEGAS >>repository to the whole VERITAS collaboration. They are used at a wide >>variety of other collaborating >> institutions. A separate and important part of this project is to also >>analyze and publish AGN spectra and dark matter limits. Also, a project >>to determine electron spectra and >> Cosmic Ray electron/positron spectra ratios is underway that require >>substantial resources. >> >> >> >> Project description: This Fusion allocation improves the science >>reach of VERITAS and allows us to complete the work in a timely fashion >>resulting in publications. The analysis of these data sets is >>computationally intensive, requiring a few TB of disk space and of order >>100 processors for a few hours at a time. In conjunction with this, the >>users of this allocation are developers for the VEGAS code base. We >>focus on improving the sensitivity of the instrument through improved >>photon angular and energy reconstruction. This work involves a >>substantial amount of simulation processing to study >> in detail the photon detection scheme and make the look-up tables that >>characterize the transfer function of the detector. To produce >>production quality reconstruction algorithms, we also optimize the >>analysis for real sources. Fusion is well suited to this type of >>workload. >> >> Developing new algorithms for analyzing VERITAS data >> in order to improve sensitivity, lower energy threshold and improve >>energy resolution is an ongoing goal. This past year through work on >>this project at NERSC, we have be able >> enabled to fully implement an analysis method that almost doubles the >>e?ffective fi?eld of view of the array. Substantial simulations are used >>to verify the accuracy of the method >> so that its results can be used in publications. This method will >>become an optional analysis method with the next release of VEGAS. A >>second new method, Model 3D, now being developed with this project >>promises to further improve the analysis energy >> resolution and energy threshold. We expect to be able to o?er this >>method as a standard analysis method this coming fall. >> Project URL: http://veritas.sao.arizona.edu/ >> Requested allocation: 200000 >> Q1: 100000 >> Q2: 50000 >> Q3: 25000 >> Q4: 25000 >> Justification: >> >> >> The requester has used undetermined amount hours of their initial >>startup project. >> >> In addition to approving an initial amount, please specify a Category >> and Subcategory for this project. For a list of the current selection >> of approved categories, please see: >> >> https://wiki.lcrc.anl.gov/wiki/Processes/Categories >> >> Once the Allocation committee has approved the project, please go to >> the Project Management page to create it: >> >> https://accounts.lcrc.anl.gov/projects.php >> >> Thank You, >> The LCRC Accounts System > >_______________________________________________ >allocations-admins mailing list >allocations-admins(a)lists.lcrc.anl.gov >https://lists.lcrc.anl.gov/mailman/listinfo/allocations-admins

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Re: [allocations-admins] [LCRC Accounts] Project Request: VERITAS
by John Valdes 03 Oct '13

03 Oct '13

Forgot that this new project came in on Tue. OK to approve the full 200K for the full FY? One concern is that the PI says analysis will involve a "few TB of disk" which we currently don't have (but will soon). My take on the metadata (please correct): PoC: Steve Pieper Pri: 3 Cat: P Sub: Phy John On Tue, Oct 01, 2013 at 03:11:50PM -0500, accounts(a)lcrc.anl.gov wrote: > Hello, > > A new project on the LCRC cluster has been requested. Please forward > the information on to the LCRC Allocation sub-committee. > > Applicant's name: Benjamin Zitzer > Applicant's institution: ANL > Applicant's division: HEP > Project Name: VERITAS > Project title: KASCADE Simulations for VERITAS > Associated funding: DOE > Other Systems: NERSC at Berkley, 400,000 hours plus an 200,000 extension > Hansen at Purdue University, 400,000 hours (not allocated) > Science: VERITAS, the Very Energetic Radiation Imaging Telescope Array > System, located in Southern Arizona at the Whipple Observatory Base camp, is an array of imaging atmospheric Cherenkov telescopes designed to detect very-high-energy (VHE) > gamma rays (85 GeV - 50 TeV) that shower in the earth's atmosphere. VHE energy spectra of active galaxies, pulsars, and the associated pulsar wind nebulae are now able > in many cases to constrain models of the acceleration mechanisms responsible for the photon production. Constraints are usually even stronger when we perform a simultaneous > multi-wavelength analysis by combining VERITAS spectra with other spectra from partner observatories. > The results of our work are distributed through releases of the VEGAS repository to the whole VERITAS collaboration. They are used at a wide variety of other collaborating > institutions. A separate and important part of this project is to also analyze and publish AGN spectra and dark matter limits. Also, a project to determine electron spectra and > Cosmic Ray electron/positron spectra ratios is underway that require substantial resources. > > > > Project description: This Fusion allocation improves the science reach of VERITAS and allows us to complete the work in a timely fashion resulting in publications. The analysis of these data sets is computationally intensive, requiring a few TB of disk space and of order 100 processors for a few hours at a time. In conjunction with this, the users of this allocation are developers for the VEGAS code base. We focus on improving the sensitivity of the instrument through improved photon angular and energy reconstruction. This work involves a substantial amount of simulation processing to study > in detail the photon detection scheme and make the look-up tables that characterize the transfer function of the detector. To produce production quality reconstruction algorithms, we also optimize the analysis for real sources. Fusion is well suited to this type of workload. > > Developing new algorithms for analyzing VERITAS data > in order to improve sensitivity, lower energy threshold and improve energy resolution is an ongoing goal. This past year through work on this project at NERSC, we have be able > enabled to fully implement an analysis method that almost doubles the effective field of view of the array. Substantial simulations are used to verify the accuracy of the method > so that its results can be used in publications. This method will become an optional analysis method with the next release of VEGAS. A second new method, Model 3D, now being developed with this project promises to further improve the analysis energy > resolution and energy threshold. We expect to be able to oer this method as a standard analysis method this coming fall. > Project URL: http://veritas.sao.arizona.edu/ > Requested allocation: 200000 > Q1: 100000 > Q2: 50000 > Q3: 25000 > Q4: 25000 > Justification: > > > The requester has used undetermined amount hours of their initial startup project. > > In addition to approving an initial amount, please specify a Category > and Subcategory for this project. For a list of the current selection > of approved categories, please see: > > https://wiki.lcrc.anl.gov/wiki/Processes/Categories > > Once the Allocation committee has approved the project, please go to > the Project Management page to create it: > > https://accounts.lcrc.anl.gov/projects.php > > Thank You, > The LCRC Accounts System

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[LCRC Accounts] Project Request: VERITAS
by accounts＠lcrc.anl.gov 01 Oct '13

01 Oct '13

Hello, A new project on the LCRC cluster has been requested. Please forward the information on to the LCRC Allocation sub-committee. Applicant's name: Benjamin Zitzer Applicant's institution: ANL Applicant's division: HEP Project Name: VERITAS Project title: KASCADE Simulations for VERITAS Associated funding: DOE Other Systems: NERSC at Berkley, 400,000 hours plus an 200,000 extension Hansen at Purdue University, 400,000 hours (not allocated) Science: VERITAS, the Very Energetic Radiation Imaging Telescope Array System, located in Southern Arizona at the Whipple Observatory Base camp, is an array of imaging atmospheric Cherenkov telescopes designed to detect very-high-energy (VHE) gamma rays (85 GeV - 50 TeV) that shower in the earth's atmosphere. VHE energy spectra of active galaxies, pulsars, and the associated pulsar wind nebulae are now able in many cases to constrain models of the acceleration mechanisms responsible for the photon production. Constraints are usually even stronger when we perform a simultaneous multi-wavelength analysis by combining VERITAS spectra with other spectra from partner observatories. The results of our work are distributed through releases of the VEGAS repository to the whole VERITAS collaboration. They are used at a wide variety of other collaborating institutions. A separate and important part of this project is to also analyze and publish AGN spectra and dark matter limits. Also, a project to determine electron spectra and Cosmic Ray electron/positron spectra ratios is underway that require substantial resources. Project description: This Fusion allocation improves the science reach of VERITAS and allows us to complete the work in a timely fashion resulting in publications. The analysis of these data sets is computationally intensive, requiring a few TB of disk space and of order 100 processors for a few hours at a time. In conjunction with this, the users of this allocation are developers for the VEGAS code base. We focus on improving the sensitivity of the instrument through improved photon angular and energy reconstruction. This work involves a substantial amount of simulation processing to study in detail the photon detection scheme and make the look-up tables that characterize the transfer function of the detector. To produce production quality reconstruction algorithms, we also optimize the analysis for real sources. Fusion is well suited to this type of workload. Developing new algorithms for analyzing VERITAS data in order to improve sensitivity, lower energy threshold and improve energy resolution is an ongoing goal. This past year through work on this project at NERSC, we have be able enabled to fully implement an analysis method that almost doubles the effective field of view of the array. Substantial simulations are used to verify the accuracy of the method so that its results can be used in publications. This method will become an optional analysis method with the next release of VEGAS. A second new method, Model 3D, now being developed with this project promises to further improve the analysis energy resolution and energy threshold. We expect to be able to oer this method as a standard analysis method this coming fall. Project URL: http://veritas.sao.arizona.edu/ Requested allocation: 200000 Q1: 100000 Q2: 50000 Q3: 25000 Q4: 25000 Justification: The requester has used undetermined amount hours of their initial startup project. In addition to approving an initial amount, please specify a Category and Subcategory for this project. For a list of the current selection of approved categories, please see: https://wiki.lcrc.anl.gov/wiki/Processes/Categories Once the Allocation committee has approved the project, please go to the Project Management page to create it: https://accounts.lcrc.anl.gov/projects.php Thank You, The LCRC Accounts System

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Re: [allocations-admins] [LCRC Accounts] Yearly Allocation Request from Solar_Forecasting
by John Valdes 30 Sep '13

30 Sep '13

FYI, this was me resubmitting this request for FY14 (recall the PI had submitted this request in late FY13, but wanted it to continue as requested in FY14). John On Mon, Sep 30, 2013 at 08:13:23PM -0500, accounts(a)lcrc.anl.gov wrote: > Hello, > > A yearly allocation for the LCRC cluster has been requested with the > following updated information: > > Submitter/PI: Edwin Campos > Project Name: Solar_Forecasting > Division: EVS > Project title: Multi-Model Machine-Learning Solar Forecasting Technology > Associated funding: DOE EERE SunShot > Other Systems: None. > Science: The objectives of this 3-year project (starting Aug. 2013) are as follows: > -Step 1: Perform seminal research to improve modeling and forecasting of solar irradiance. > -Step 2: Apply research results obtained from Step 1 (previous) to develop solar power forecasts. > -Step 3: Validate developed solar forecasts to meet target values of pre-existing standard metrics. > > Project description: Current weather forecast inaccuracies often result in substantial economic losses, as the electric grid operators must continuously balance supply and demand to maintain the reliability of the power grid. Failures to predict solar energy generation accurately will undoubtedly constrain the national expansion of renewable energy. The relevant weather variable to forecast here is solar-irradiance, and its rapid variations are primarily due to cloud movement, cloud formation and dissipation. > > There are several technology barriers ??? such as forecast inputs integration, forecasts output integration, scalability of forecasting tools, and numerical representation of relevant cloud processes ??? that must be overcome for improving solar forecast accuracies to a useful level, if solar energy were to be become a dependable source of energy > > This project proposes to overcome these barriers by using novel machine-learning algorithms and hi-performance computers. The project will demonstrate that transformational improvements are possible on solar forecasting ??? for periods between 0 to 6 hours (including power ramps) and the day ahead ??? by determining optimal combinations for observations of thermodynamic profiles measured over a solar power plant, measured cloud motions in the area (e.g., from remote sensing observations at high resolution) and routine forecast outputs from numerical weather models. > > We are a team of 6 Argonne researchers, working in coordination with a new Research Consortium lead by IBM. We will develop advanced cloud and radiative transfer computations, as well as machine learning algorithms based on the self-adjusting voting algorithms of the Watson computer (http://en.wikipedia.org/wiki/Watson_%28computer%29) > Project URL: http://solarhighpen.energy.gov/project/ibm_thomas_j_watson_research_center_… > Current FY Hours Used: undetermined amount > > New FY Requested allocation: 200000 > Q1: 50000 > Q2: 50000 > Q3: 50000 > Q4: 50000 > > Justification: > > Thank You, > > The LCRC Accounts System > _______________________________________________ > allocations-admins mailing list > allocations-admins(a)lists.lcrc.anl.gov > https://lists.lcrc.anl.gov/mailman/listinfo/allocations-admins

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[LCRC Accounts] Yearly Allocation Request from Solar_Forecasting
by accounts＠lcrc.anl.gov 30 Sep '13

30 Sep '13

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Edwin Campos Project Name: Solar_Forecasting Division: EVS Project title: Multi-Model Machine-Learning Solar Forecasting Technology Associated funding: DOE EERE SunShot Other Systems: None. Science: The objectives of this 3-year project (starting Aug. 2013) are as follows: -Step 1: Perform seminal research to improve modeling and forecasting of solar irradiance. -Step 2: Apply research results obtained from Step 1 (previous) to develop solar power forecasts. -Step 3: Validate developed solar forecasts to meet target values of pre-existing standard metrics. Project description: Current weather forecast inaccuracies often result in substantial economic losses, as the electric grid operators must continuously balance supply and demand to maintain the reliability of the power grid. Failures to predict solar energy generation accurately will undoubtedly constrain the national expansion of renewable energy. The relevant weather variable to forecast here is solar-irradiance, and its rapid variations are primarily due to cloud movement, cloud formation and dissipation. There are several technology barriers – such as forecast inputs integration, forecasts output integration, scalability of forecasting tools, and numerical representation of relevant cloud processes – that must be overcome for improving solar forecast accuracies to a useful level, if solar energy were to be become a dependable source of energy This project proposes to overcome these barriers by using novel machine-learning algorithms and hi-performance computers. The project will demonstrate that transformational improvements are possible on solar forecasting – for periods between 0 to 6 hours (including power ramps) and the day ahead – by determining optimal combinations for observations of thermodynamic profiles measured over a solar power plant, measured cloud motions in the area (e.g., from remote sensing observations at high resolution) and routine forecast outputs from numerical weather models. We are a team of 6 Argonne researchers, working in coordination with a new Research Consortium lead by IBM. We will develop advanced cloud and radiative transfer computations, as well as machine learning algorithms based on the self-adjusting voting algorithms of the Watson computer (http://en.wikipedia.org/wiki/Watson_%28computer%29) Project URL: http://solarhighpen.energy.gov/project/ibm_thomas_j_watson_research_center_… Current FY Hours Used: undetermined amount New FY Requested allocation: 200000 Q1: 50000 Q2: 50000 Q3: 50000 Q4: 50000 Justification: Thank You, The LCRC Accounts System

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