ComputingandSoftwarePublicResults < AtlasPublic

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---+!! <nop> Computing and Software - Public Results

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---+ Introduction

<!-- Add an introduction here, describing the purpose of this topic. -->

On this page public results and material concerning ATLAS Computing and Software is collected...

---+ Computing TDR and related Documents

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| *report* | *links* | *year* |
| Update of Computing Models for Run-2 | [[https://cds.cern.ch/record/1695401/?ln=en][CDS]] | 2014 |
| Computing TDR | [[https://cds.cern.ch/record/837738/?ln=en][CDS]] | 2005 |
| Computing Model Document | [[https://cds.cern.ch/record/811058/?ln=en][CDS]] | 2004 |
| Technical Proposal | [[https://cds.cern.ch/record/322322/?ln=en][CDS]] | 1996 |

---+ Public Notes, Conference Proceedings and Slides

<!-- A complete list of ATLAS computing and software public notes can be found on CDS. A lot of material is as well available on recent computing and software related talks and proceedings at international conferences. -->

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| *type of public documents* | *links* |
| list of ATLAS-SOFT-PUB notes | [[https://cds.cern.ch/search?ln=en&as=1&cc=ATLAS+Notes&m1=a&p1=ATL+SOFT+PUB&f1=reportnumber&op1=a&m2=a&p2=&f2=&op2=a&m3=a&p3=&f3=&action_search=Search&c=ATLAS+Notes&c=&sf=&so=d&rm=&rg=10&sc=1&of=hb][CDS]] |
| list of conference proceedings | [[https://cds.cern.ch/search?ln=en&as=1&cc=ATLAS+Notes&m1=a&p1=ATL+SOFT+PROC&f1=reportnumber&op1=a&m2=a&p2=&f2=&op2=a&m3=a&p3=&f3=&action_search=Search&c=ATLAS+Notes&c=&sf=&so=d&rm=&rg=10&sc=1&of=hb][CDS]] |
| list of conference talks | [[https://cds.cern.ch/search?ln=en&as=1&cc=ATLAS+Notes&m1=a&p1=ATL+SOFT+SLIDE&f1=reportnumber&op1=a&m2=a&p2=&f2=&op2=a&m3=a&p3=&f3=&action_search=Search&c=ATLAS&c=&sf=&so=d&rm=&rg=10&sc=1&of=hb][CDS]] |

---+ Recent Public Plots

<table  bgcolor="#f5f5fa" cellspacing="10" cellpadding="10" border="1"> <tbody> 

<tr>
<td bgcolor="#eeeeee"> 
Estimated total disk resources (in PBytes) needed for the years 2018 to 2032 for both data and simulation processing. The plot updates the projection made in 2017 which was based on the Run-2 computing model and with updated LHC expected running conditions. The blue points show the improvements possible in two different scenarios, which require significant development work (1) top curve, reduction of AOD and DAOD size of 30% compared to the Run-2 trend, bottom curve further reduction with the inclusion of a common DAOD format to be used by most analysis, removal of previous year AODs from disk and the storage of only one DAOD version. The solid line shows the amount of resources expected to be available if a flat funding scenario is assumed, which implies an increase of 15% per year, based on the current technology trends.  
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/diskHLLHC_noold.png" alt="diskHLLHC_noold.png" /> <br>
 [[%ATTACHURL%/diskHLLHC_noold.pdf][pdf-file]], [[%ATTACHURL%/diskHLLHC_noold.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
Estimated total disk resources (in PBytes) needed for the years 2018 to 2032 for both data and simulation processing. The plot updates the projection made in 2017 which was based on the Run-2 computing model and with updated LHC expected running conditions. The brown points are estimates made in 2017 and based on the current event sizes and using the ATLAS computing model parameters from 2017. The blue points show the improvements possible in two different scenarios, which require significant development work: (1) top curve, reduction of AOD and DAOD size of 30% compared to the Run-2 trend, bottom curve further reduction with the inclusion of a common DAOD format to be used by most analysis, removal of previous year AODs from disk and the storage of only one DAOD version. The solid line shows the amount of resources expected to be available if a flat funding scenario is assumed, which implies an increase of 15% per year, based on the current technology trends.  
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/diskHLLHC_18.png" alt="diskHLLHC_18.png" /> <br>
 [[%ATTACHURL%/diskHLLHC_18.pdf][pdf-file]], [[%ATTACHURL%/diskHLLHC_18.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Fraction of disk resources needed in 2028 at the end of Run-4 for different data types. This plot: assuming a reduction in size of 30% of AOD and DAOD.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/disk2028_baseline.png" alt="disk2028_baseline.png" /> <br>
 [[%ATTACHURL%/disk2028_baseline.pdf][pdf-file]], [[%ATTACHURL%/disk2028_baseline.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Fraction of disk resources needed in 2028 at the end of Run-4 for different data types. This plot: a further reduction with the inclusion of a common DAOD format to be used by most analysis, removal of previous year AODs from disk and the storage of only one DAOD version. 
.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/disk2028_reduced.png" alt="disk2028_reduced.png" /> <br>
 [[%ATTACHURL%/disk2028_reduced.pdf][pdf-file]], [[%ATTACHURL%/disk2028_reduced.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
Estimated CPU resources (in MHS06) needed for the years 2018 to 2032 for both data and simulation processing. The plot updates the projection made in 2017 (which was based on the Run-2 computing model) with updated LHC running conditions and revised scenarios for future computing models. The blue points show the improvements possible in three different scenarios, which require significant development work: (1) top curve with fast calo sim used for 75% of the Monte Carlo simulation; (2) middle curve using in addition a faster version of reconstruction, which is seeded by the event generator information; (3) bottom curve, where the time spent in event generation is halved, either by software improvements or re-using some of the events.  The solid line shows the amount of resources expected to be available if a flat funding scenario is assumed, which implies an increase of 20% per year, based on the current technology trends.  
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/cpuHLLHC_noold.png" alt="cpuHLLHC_noold.png" /> <br>
 [[%ATTACHURL%/cpuHLLHC_noold.pdf][pdf-file]], [[%ATTACHURL%/cpuHLLHC_noold.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Estimated CPU resources (in MHS06) needed for the years 2018 to 2032 for both data and simulation processing. The plot updates the projection made in 2017 (which was based on the Run-2 computing model) with updated LHC running conditions and revised scenarios for future computing models. The brown points are estimates made in 2017, based on the current software performance estimates and using the ATLAS computing model parameters from 2017. The blue points show the improvements possible in three different scenarios, which require significant development work: (1) top curve with fast calo sim used for 75% of the Monte Carlo simulation; (2) middle curve using in addition a faster version of reconstruction, which is seeded by the event generator information; (3) bottom curve, where the time spent in event generation is halved, either by software improvements or by re-using some of the events.  The solid line shows the amount of resources expected to be available if a flat funding scenario is assumed, which implies an increase of 20% per year, based on the current technology trends.  
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/cpuHLLHC_18.png" alt="cpuHLLHC_18.png" /> <br>
 [[%ATTACHURL%/cpuHLLHC_18.pdf][pdf-file]], [[%ATTACHURL%/cpuHLLHC_18.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Fraction of CPU resources needed in 2028 at the end of Run-4 for different processing workflows.The “MC-Full” section in green is related to the fraction of time spent on the full AtlasG4 simulation and divided in a simulation part “(Sim)” for the Geant4 simulation and a reconstruction part “(Rec)” accounting the time spent reconstructing the events. Similarly, the “MC-Fast” section in red shows this distribution for the time spent running the Fast Calo simulation.  This plot: using fast calo sim for 75% of the Monte Carlo simulation and standard reconstruction.  </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/cpu2028.png" alt="cpu2028.png" /> <br>
 [[%ATTACHURL%/cpu2028.pdf][pdf-file]], [[%ATTACHURL%/cpu2028.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
Fraction of CPU resources needed in 2028 at the end of Run-4 for different processing workflows.The “MC-Full” section in green is related to the fraction of time spent on the full AtlasG4 simulation and divided in a simulation part “(Sim)” for the Geant4 simulation and a reconstruction part “(Rec)” accounting the time spent reconstructing the events. Similarly, the “MC-Fast” section in red shows this distribution for the time spent running the Fast Calo simulation.  This plot: using in addition a faster version of reconstruction, which is seeded by the event generator information, and assuming event generation is sped up by a factor of two. 
</td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/cpu2028_fast.png" alt="cpu2028_fast.png" /> <br>
 [[%ATTACHURL%/cpu2028_fast.pdf][pdf-file]], [[%ATTACHURL%/cpu2028_fast.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
OBSOLETE: Estimated total disk resources (in PBytes) needed for the years 2018 to 2028 for both data and simulation processing. The blue points are estimates based on the current event sizes estimates and using the ATLAS computing model parameters from 2017. The solid line shows the amount of resources expected to be available if a flat funding scenario is assumed, which implies an increase of 15% per year, based on the current technology trends.   
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/diskHLLHC.png" alt="diskHLLHC.png" /> <br>
 [[%ATTACHURL%/diskHLLHC.pdf][pdf-file]], [[%ATTACHURL%/diskHLLHC.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
 OBSOLETE: Estimated CPU resources (in kHS06) needed for the years 2018 to 2028 for both data and simulation processing. The blue points are estimates based on the current software performance estimates and using the ATLAS computing model parameters from 2017. The solid line shows the amount of resources expected to be available if a flat funding scenario is assumed, which implies an increase of 20% per year, based on the current technology trends.  
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/cpuHLLHC.png" alt="cpuHLLHC.png" /> <br>
 [[%ATTACHURL%/cpuHLLHC.pdf][pdf-file]], [[%ATTACHURL%/cpuHLLHC.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
The dependency of reconstruction wall time per event on the average number of interactions per bunch crossing (<&#956;>) is shown for the current Inner Detector reconstruction with default tracking cuts. The plot contains a selection of reconstructed luminosity blocks of RAW data from 13 !TeV pp LHC collisions in 2017. An ATLAS luminosity block typically corresponds to one minute of data-taking. Tier-0 reconstruction jobs were required to run in single-core mode on a selected sub-cluster of 16-core machines (with Intel(R) Xeon(R) CPU E5-2630 v3 of 2.40 GHz clock speed, memory of 4 GB/core, 21 HS06/core with HT off). The typical collision runs (blue scatter plot) can be only qualitatively compared with the performance in high-&#956; run 335302 (red boxes), which had special data-taking conditions. Furthermore, the high-&#956; run jobs were configured to produce only AOD outputs, whereas standard jobs proceeded with 12 additional output types (different DRAW, DESD, DAOD and HIST), which takes extra processing time. The behaviour of the tracking reconstruction, which dominates the CPU use at high pileup, for High Luminosity LHC conditions with an upgraded tracking detector has been studied in reference [1].%BR%%BR%
[1] "Technical Design Report for the ATLAS ITk Pixel Detector", ATLAS Collaboration, CERN-LHCC-2017-021, ATLAS-TDR-030, Geneva 2018.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/reco_WtPerEvent_NOfit_revised.png" alt="reco_WtPerEvent_NOfit_revised.png" /> <br>
 [[%ATTACHURL%/reco_WtPerEvent_NOfit_revised.pdf][pdf-file]], [[%ATTACHURL%/reco_WtPerEvent_NOfit_revised.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
Digitization time per event, in HepSpec06 seconds, as a function of the average number of interactions per bunch crossing, with 25 ns bunch spacing. A linear fit to the times is overlaid. On a modern CPU, one second of wall clock time corresponds to about 10 HepSpec06 seconds. </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/cpuVSmu_all.png" alt="icpuVSmu_all.png" /> <br>
 [[%ATTACHURL%/cpuVSmu_all.pdf][pdf-file]], [[%ATTACHURL%/cpuVSmu_all.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
On this figure the total reconstruction time per event is shown for a top Monte Carlo simulation sample with 40 pileup at 13 !TeV, 25 ns bunch spacing. An overall improvement of a factor 3 is visible comparing the 2012 Tier-0 release (17.2.7.9), the release 19.0.3.3 which is optimised for reconstruction of the Run-1 data and the release 19.1.1.1 which is optimised for reconstructing Run-2 data. The CPU time is shown as well separately for the Inner Detector reconstruction as the tracking is dominating the total resource needs. The simulation is done using a Run-1 detector geometry without the IBL. The HS06 scaling factor for the machine used for this study is quoted as 11.95.
This is the updated comparison of the CPU time for reconstructing top pair events with Run-2 pileup in different releases, including the MC15 production release (candidate), showing a speedup factor exceeding 4.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/id_evtloop_cpu_time-CHEP2015.png" alt="id_evtloop_cpu_time-CHEP2015.png" /> <br>
 [[%ATTACHURL%/id_evtloop_cpu_time-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/id_evtloop_cpu_time-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Event-wise fractional overlaps between derivations built from the muon stream, run 203875 (2012) using 5000 input events. Each cell of the plot displays the fraction of events accepted in the first format that are also accepted in the second. A higher number indicates that more events are shared between the two formats. Since the different formats contain very different numbers of events, a cell indicating the overlap of format A with format B may not have the same value as its counterpart in the other half of the square representing the overlap of B with A. Also it should be noted that these plots cover only event-wise overlaps: overlaps in variables are not displayed. Hence, it is possible that a pair of formats may be fully correlated in terms of the events selected, but may contain orthogonal sets of variables - in which case no information is shared. Finally, it can clearly be seen that overlaps vary strongly with the trigger stream producing the events.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/muonOverlaps-CHEP2015.png" alt="muonOverlaps-CHEP2015.png" /> <br>
 [[%ATTACHURL%muonOverlaps-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/muonOverlaps-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Event-wise fractional overlaps between derivations built from the e-gamma stream, produced from run 203875 (2012) using 5000 input events. Each cell of the plot displays the fraction of events accepted in the first format that are also accepted in the second. A higher number indicates that more events are shared between the two formats. Since the different formats contain very different numbers of events, a cell indicating the overlap of format A with format B may not have the same value as its counterpart in the other half of the square representing the overlap of B with A. Also it should be noted that these plots cover only event-wise overlaps: overlaps in variables are not displayed. Hence, it is possible that a pair of formats may be fully correlated in terms of the events selected, but may contain orthogonal sets of variables - in which case no information is shared. Finally, it can clearly be seen that overlaps vary strongly with the trigger stream producing the events.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/egammaOverlaps-CHEP2015.png" alt="egammaOverlaps-CHEP2015.png" /> <br>
 [[%ATTACHURL%egammaOverlaps-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/egammaOverlaps-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Event-wise fractional overlaps between derivations built from the jet stream, run 203875 (2012) using 5000 input events. Each cell of the plot displays the fraction of events accepted in the first format that are also accepted in the second. A higher number indicates that more events are shared between the two formats. Since the different formats contain very different numbers of events, a cell indicating the overlap of format A with format B may not have the same value as its counterpart in the other half of the square representing the overlap of B with A. Also it should be noted that these plots cover only event-wise overlaps: overlaps in variables are not displayed. Hence, it is possible that a pair of formats may be fully correlated in terms of the events selected, but may contain orthogonal sets of variables - in which case no information is shared. Finally, it can clearly be seen that overlaps vary strongly with the trigger stream producing the events.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/jetsOverlaps-CHEP2015.png" alt="jetsOverlaps-CHEP2015.png" /> <br>
 [[%ATTACHURL%jetsOverlaps-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/jetsOverlaps-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Memory profile of ATLAS MC digitization and reconstruction jobs comparing total RSS of 8 serial jobs to RSS of one <nop>AthenaMP job with 8 worker processes. Memory savings at the reconstruction step of this particular job are ~45%.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/AthenaMP-vs-Serial-19.1.1.5-pileup-CHEP2015.png" alt="AthenaMP-vs-Serial-19.1.1.5-pileup-CHEP2015.png" /> <br>
 [[%ATTACHURL%AthenaMP-vs-Serial-19.1.1.5-pileup-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/AthenaMP-vs-Serial-19.1.1.5-pileup-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
<nop>AthenaMP schematic view </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/Atlas-AthenaMP-Schematic-CHEP2015.png" alt="Atlas-AthenaMP-Schematic-CHEP2015.png" /> <br>
 [[%ATTACHURL%Atlas-AthenaMP-Schematic-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/Atlas-AthenaMP-Schematic-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
<nop>Yoda scaling with number of parallel processors (cores). The plot shows how the event throughput of Atlas G4 simulation scales with number of parallel processors (cores) when running within Yoda system on the Edison HPC at NERSC (Berkeley). The scalability is already quite good, although there is certainly a room for improvement and we will be looking into it in the coming months.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/ATLAS-Yoda-Sim-Throughput-CHEP2015.png" alt="ATLAS-Yoda-Sim-Throughput-CHEP2015.png" /> <br>
 [[%ATTACHURL%ATLAS-Yoda-Sim-Throughput-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/ATLAS-Yoda-Sim-Throughput-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Size of <nop>DxAOD (derivation) datasets as a fraction of the size of the parent xAOD datasets, evaluated for all derivation types across all runs in period B, for the three physics streams. Each entry in the histogram represents a single derived dataset, with the value being equal to the size of the dataset divided by the size of its parent (input) dataset. There are a total of 65 formats, three streams and more than 100 runs, leading to several thousand individual datasets.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/size-CHEP2015.png" alt="size-CHEP2015.png" /> <br>
 [[%ATTACHURL%size-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/size-CHEP2015.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Fraction of total input events written into the <nop>DxAOD (derivation) datasets, evaluated for all derivation types across all runs in period B, for the three physics streams. Each entry in the histogram represents a single derived dataset, with the value being equal to the number of selected events in the dataset divided by the number of input events. There are a total of 65 formats, three streams and more than 100 runs, leading to several thousand individual datasets.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/skim-CHEP2015.png" alt="skim-CHEP2015.png" /> <br>
 [[%ATTACHURL%skim-CHEP2015.pdf][pdf-file]], [[%ATTACHURL%/skim-CHEP2015.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
The rate of new data transformations added to the ATLAS production system.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/transformations.png" alt="transformations.png" /> <br>
 [[%ATTACHURL%transformations.pdf][pdf-file]], [[%ATTACHURL%/transformations.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Monthly rate of task requests submitted to the ATLAS production system.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/tasks.png" alt="tasks.png" /> <br>
 [[%ATTACHURL%tasks.pdf][pdf-file]], [[%ATTACHURL%/tasks.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Comparison of monthly rates of task requests in the ATLAS production systems ProdSys1 and ProdSys2.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/comparison.png" alt="comparison.png" /> <br>
 [[%ATTACHURL%comparison.pdf][pdf-file]], [[%ATTACHURL%/comparison.png][png-file]] 
 </td> </tr>


<tr>
<td bgcolor="#eeeeee"> 
Comparison of the energy loss distributions for 1 GeV single muon tracks in the ATLAS Pixel and SCT Detectors for full simulation (based on the Geant4 toolkit) and FATRAS simulation.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/Muon_1GeV_DeltaP_2.png" alt="Muon_1GeV_DeltaP_2.png" /> <br>
 [[%ATTACHURL%Muon_1GeV_DeltaP_2.pdf][pdf-file]], [[%ATTACHURL%/Muon_1GeV_DeltaP_2.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Comparison of the energy loss eta distributions for 1 GeV single muon tracks in the ATLAS Pixel and SCT Detectors for full simulation (based on the Geant4 toolkit) and FATRAS simulation.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/Muon_1GeV_Eta_DeltaEProfile_3.png" alt="Muon_1GeV_Eta_DeltaEProfile_3.png" /> <br>
 [[%ATTACHURL%Muon_1GeV_Eta_DeltaEProfile_3.pdf][pdf-file]], [[%ATTACHURL%/Muon_1GeV_Eta_DeltaEProfile_3.png][png-file]] 
 </td> </tr>

<tr>
<td bgcolor="#eeeeee"> 
Comparison of hit distribution of single muon tracks in the ATLAS Pixel and SCT Detectors using FATRAS tracking geometry from GeoModel and from XML configuration file.
 </td>
 <td align="center">
 <img width="300" src="%ATTACHURLPATH%/myplotRZ.png" alt="myplotRZ.png" /> <br>
 [[%ATTACHURL%/myplotRZ.pdf][pdf-file]], [[%ATTACHURL%/myplotRZ.png][png-file]] 
 </td> </tr>


</table>


<center>
<img alt="/FCS_pions_layer10.png" src="%ATTACHURLPATH%/FCS_pions_layer10_prelim.png" width="500" />
</center>
Fig. 3: Energy fraction deposited in the 3rd layer of the Hadronic Endcap calorimeter by charged pions. The black points show the Geant4 inputs, and the result of the longitudinal
energy parametrisation is shown in light blue. A good agreement is observed. The results of a Kolmogorov (KS) and chi2 test are displayed as well.

<center>
<img alt="/FCS_photons_totalE.png" src="%ATTACHURLPATH%/FCS_photons_totalE_prelim.png" width="500" />
</center>
Fig. 4: Total cell energy deposited in the calorimeter by photons. The black points show the Geant4 inputs, and the result of the longitudinal energy
parametrisation is shown in light blue. A good agreement is observed. The results of a Kolmogorov (KS) and chi2 test are displayed as well.



(a)
<center>
<img src="%ATTACHURLPATH%/Closure_noWiggle.png" alt="Closure_noWiggle.png" width="500" /></verbatim>
</center>

(b)
<center>
 <img src="%ATTACHURLPATH%/Closure_withWiggle.png" alt="Closure_withWiggle.png" width="500" /></verbatim>
</center>
Fig. 4: The ratio of the FastCaloSim energy profile and the reconstructed cells energy profile, as a function of the distance of the centre of the cell and the pion calorimeter entrance position deta(pi,cell), dphi(pi,cell), for the original hit-cell assignment with the simplified geometry (a) and the modified hit-cell assignment using the wiggle hit displacement method (b). The bias in phi due to the wrong description of the accordion shape of the calorimeter in the simplified geometry is greatly reduced when using the hit displacement method.



<center>
<img alt="NNeur4_Lay1_E50000_eta0.20_PID211_reference_polar.png" src="%ATTACHURLPATH%/NNeur4_Lay1_E50000_eta0.20_PID211_reference_polar.png" width="500" />
</center>
Fig. 5: Illustration of the energy normalized per bin area used as input to the NN fit. This example is for 50 GeV central (0.20<|eta|<0.25) pions in the EMB1 layer and corresponds to events included in the first bin of the PCA energy parameterisation. 

<center>
<img alt="NNeur4_Lay1_E50000_eta0.20_PID211_NNoutput_polar.png" src="%ATTACHURLPATH%/NNeur4_Lay1_E50000_eta0.20_PID211_NNoutput_polar.png" width="500" />
</center>
Fig. 6: Illustration of the output of the NN parametrisation of Fig.9 input. This example is for 50 GeV central (0.20<|eta|<0.25) pions in the EMB1 layer and corresponds to events included in the first bin of the PCA energy parameterisation. 



---+ Furthermore

More material is available elsewhere concerning related activities, such as:
   * [[SimulationPublicResults][ATLAS simulation public results]]
   * [[MCPublicResults][ATLAS Monte Carlo public results]]
   * [[EventDisplayPublicResults][ATLAS event displays public results]]
All ATLAS public results can be found [[https://twiki.cern.ch/twiki/bin/view/AtlasPublic][here]].

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---

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Topic attachments
I	Attachment	History	Action	Size	Date	Who
pdf	ATLAS-Yoda-Sim-Throughput-CHEP2015.pdf	r1	manage	13.7 K	2015-04-01 - 12:18	EricLancon
png	ATLAS-Yoda-Sim-Throughput-CHEP2015.png	r1	manage	8.4 K	2015-04-01 - 12:18	EricLancon
pdf	AthenaMP-vs-Serial-19.1.1.5-pileup-CHEP2015.pdf	r1	manage	17.9 K	2015-04-01 - 12:18	EricLancon
png	AthenaMP-vs-Serial-19.1.1.5-pileup-CHEP2015.png	r1	manage	10.3 K	2015-04-01 - 12:18	EricLancon
pdf	Atlas-AthenaMP-Schematic-CHEP2015.pdf	r1	manage	62.5 K	2015-04-01 - 12:18	EricLancon
png	Atlas-AthenaMP-Schematic-CHEP2015.png	r1	manage	67.4 K	2015-04-01 - 12:18	EricLancon
png	Closure_noWiggle.png	r1	manage	99.1 K	2016-10-28 - 16:49	AndyHaas
png	Closure_withWiggle.png	r1	manage	99.5 K	2016-10-28 - 16:49	AndyHaas
pdf	FCS_photons_totalE_prelim.pdf	r1	manage	17.4 K	2016-10-28 - 16:49	AndyHaas
png	FCS_photons_totalE_prelim.png	r1	manage	36.5 K	2016-10-28 - 16:49	AndyHaas
pdf	FCS_pions_layer10_prelim.pdf	r1	manage	19.0 K	2016-10-28 - 16:49	AndyHaas
png	FCS_pions_layer10_prelim.png	r1	manage	35.9 K	2016-10-28 - 16:49	AndyHaas
pdf	Muon_1GeV_DeltaP_2.pdf	r1	manage	28.8 K	2015-05-11 - 09:38	EricLancon
png	Muon_1GeV_DeltaP_2.png	r1	manage	27.7 K	2015-05-11 - 09:38	EricLancon
pdf	Muon_1GeV_Eta_DeltaEProfile_3.pdf	r1	manage	24.0 K	2015-05-11 - 09:38	EricLancon
png	Muon_1GeV_Eta_DeltaEProfile_3.png	r1	manage	23.2 K	2015-05-11 - 09:38	EricLancon
png	NNeur4_Lay1_E50000_eta0.20_PID211_NNoutput_polar.png	r1	manage	261.8 K	2016-10-28 - 16:49	AndyHaas
png	NNeur4_Lay1_E50000_eta0.20_PID211_reference_polar.png	r1	manage	267.2 K	2016-10-28 - 16:49	AndyHaas
pdf	comparison.pdf	r1	manage	203.9 K	2015-05-11 - 09:38	EricLancon
png	comparison.png	r1	manage	226.6 K	2015-05-11 - 09:38	EricLancon
pdf	cpuVSmu_all.pdf	r1	manage	20.4 K	2016-02-17 - 00:17	EricLancon
png	cpuVSmu_all.png	r1	manage	17.5 K	2016-02-17 - 00:17	EricLancon
pdf	disk2028_baseline.pdf	r1	manage	14.3 K	2018-11-15 - 08:29	DavideCostanzo1
png	disk2028_baseline.png	r1	manage	71.8 K	2018-11-15 - 08:29	DavideCostanzo1
pdf	diskHLLHC_18.pdf	r1	manage	15.5 K	2018-11-15 - 07:46	DavideCostanzo1
pdf	egammaOverlaps-CHEP2015.pdf	r1	manage	167.6 K	2015-04-01 - 12:18	EricLancon
png	egammaOverlaps-CHEP2015.png	r1	manage	221.1 K	2015-04-01 - 12:18	EricLancon
pdf	id_evtloop_cpu_time-CHEP2015.pdf	r1	manage	82.1 K	2015-04-01 - 12:18	EricLancon
png	id_evtloop_cpu_time-CHEP2015.png	r1	manage	140.3 K	2015-04-01 - 12:18	EricLancon
pdf	id_evtloop_cpu_time.pdf	r1	manage	14.0 K	2014-08-01 - 16:50	MarkusElsing
png	id_evtloop_cpu_time.png	r1	manage	139.2 K	2014-08-01 - 16:50	MarkusElsing
pdf	jetsOverlaps-CHEP2015.pdf	r1	manage	183.3 K	2015-04-01 - 12:18	EricLancon
png	jetsOverlaps-CHEP2015.png	r1	manage	240.2 K	2015-04-01 - 12:19	EricLancon
pdf	mu_walltime_fit_combined2.pdf	r2 r1	manage	61.1 K	2018-09-17 - 14:39	JaroslavGuenther
pdf	muonOverlaps-CHEP2015.pdf	r1	manage	160.3 K	2015-04-01 - 12:18	EricLancon
png	muonOverlaps-CHEP2015.png	r1	manage	207.4 K	2015-04-01 - 12:19	EricLancon
pdf	myplotRZ.pdf	r1	manage	25.1 K	2015-05-11 - 09:39	EricLancon
png	myplotRZ.png	r1	manage	17.7 K	2015-05-11 - 09:39	EricLancon
pdf	reco_WtPerEvent_NOfit_revised.pdf	r1	manage	61.1 K	2018-09-17 - 14:35	JaroslavGuenther
png	reco_WtPerEvent_NOfit_revised.png	r1	manage	64.9 K	2018-09-17 - 14:20	JaroslavGuenther
pdf	reco_WtPerEvent_NOfit_revised_copy.pdf	r1	manage	61.1 K	2018-09-17 - 14:38	JaroslavGuenther
pdf	size-CHEP2015.pdf	r1	manage	55.9 K	2015-04-01 - 12:18	EricLancon
png	size-CHEP2015.png	r1	manage	60.8 K	2015-04-01 - 12:18	EricLancon
pdf	skim-CHEP2015.pdf	r1	manage	49.6 K	2015-04-01 - 12:18	EricLancon
png	skim-CHEP2015.png	r1	manage	52.8 K	2015-04-01 - 12:18	EricLancon
pdf	tasks-CHEP2015.pdf	r1	manage	106.5 K	2015-04-01 - 12:18	EricLancon
png	tasks-CHEP2015.png	r1	manage	128.4 K	2015-04-01 - 12:18	EricLancon
pdf	tasks.pdf	r1	manage	106.5 K	2015-05-11 - 09:39	EricLancon
png	tasks.png	r1	manage	128.4 K	2015-05-11 - 09:39	EricLancon
pdf	transformations.pdf	r1	manage	51.3 K	2015-05-11 - 09:39	EricLancon
png	transformations.png	r1	manage	61.8 K	2015-05-11 - 09:39	EricLancon

Topic revision: r11 - 2018-11-15 - DavideCostanzo1

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