maria grazia pia, infn genova trends in computing jürgen knobloch cern scientific… challenges,...
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Maria Grazia Pia, INFN Genova
Trends in ComputingTrends in Computing
Jürgen Knobloch
CERN
scientific…
Challenges, technology and social impact
Maria Grazia Pia
INFN Genovaand
Maria Grazia Pia, INFN Genova
Chandra X-ray Observatory Status Update
September 14, 1999 MSFC/CXC
CHANDRA CONTINUES TO TAKE SHARPEST IMAGES EVER; TEAM STUDIES INSTRUMENT DETECTOR CONCERN
Normally every complex space facility encounters a few problems during its checkout period; even though Chandra’s has gone very smoothly, the science and engineering team is working a concern with a portion of one science instrument. The team is investigating a reduction in the energy resolution of one of two sets of X-ray detectors in the Advanced Charge-coupled Device Imaging Spectrometer (ACIS) science instrument. A series of diagnostic activities to characterize the degradation, identify possible causes, and test potential remedial procedures is underway. The degradation appeared in the front-side illuminated Charge-Coupled Device (CCD) chips of the ACIS. The instrument’s back-side illuminated chips have shown no reduction in capability and continue to perform flawlessly.
What could be the source
of
detector damage?
Maria Grazia Pia, INFN Genova
XMM-Newton was launched on 10 December 1999
Copyright: ESAEPIC-PN image of the Coma Cluster
Maria Grazia Pia, INFN Genova
ComplexityComplexity
of physics physics of detectorsdetectors
of the environmentenvironment where they operate
Maria Grazia Pia, INFN Genova
LHC
ATLAS
LHCb
9 o
rder
s o
f m
agn
itu
de!
HiggsHiggs
all all interactionsinteractions
StorageStorageraw recording rate 0.1–1 GByte/saccumulating at 12-14 PBytes/year
ProcessingProcessing70,000 of today’s fastest PCs(~6 hours’ Intel CPU production today)
1000 person-years1000 person-years“0ffline” software effort per experiment
~5000 Physicists~5000 Physicistsaround the world, around the clock
20 years software life-span
Maria Grazia Pia, INFN Genova
Physics from the eVeV to the PeVPeV scale
Detectors,Detectors, spacecraftsspacecrafts and environmentenvironment
……to to spacespace
Courtesy of ESA
For such experiments software is often mission criticalmission criticalRequire reliabilityreliability, rigorous software engineering software engineering
standardsstandards
Courtesy UKDM, Boulby Mine
Variety of requirements from diverse applications
From deep From deep underground…underground…
Cosmic ray experimentsCourtesy of Auger
X and astronomy, gravitational waves etc.
Dark matter and experiments
Maria Grazia Pia, INFN Genova
Medical Physics
Accurate modelling of radiation sources, devices and human body
Precision of physics
Reliability
from hospitals...
...to Mars
Easy configuration and friendly interface Speed
CT image
brachytherapy radioactive source
Maria Grazia Pia, INFN Genova
…in a fast changing computing environment
……and don’t forget changes of and don’t forget changes of requirements!requirements!
Start SPS 1976
W and Z observed 1983
Start LEP 1989
End LEP 2000
hardware, software, OShardware, software, OS
WWWGrid1998
Evolution towards greater diversity we must anticipate changesanticipate changes
Maria Grazia Pia, INFN Genova
Globalisation
Sharing requirements and functionality
across diverse fields
scientific…
Maria Grazia Pia, INFN Genova
Requirement of precise models for the simulation of electromagnetic interactions
of protons down to low energy
HadrontherapHadrontherapyyCATANA
hadrontherapy
Accurate dosimetryAccurate dosimetry
Maria Grazia Pia, INFN Genova
30 m
“Electron
deflector”
CCD displacement damage: front vs. back-illuminated
30 m Si ~1.5 MeV protons
Low-E (~100 keV to few MeV), low-angle (~0°-5°) proton scattering
Variation in Efficiency with Proton Energy at various source half-angles
1.E-09
1.E-08
1.E-07
1.E-06
1.E-05
1.E-04
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
Proton Energy (MeV)
Eff
icie
ncy
EPIC 0.5 deg
EPIC 1 deg
EPIC 4 deg
EPIC 2 deg
EPIC 10 deg
EPIC 30 deg
RGS 0.5 deg
RGS 1 deg
RGS 2 deg
RGS 4 deg
RGS 10 deg
RGS 30 deg
EPIC
RGS
30 m 2 m2 m
Active layerPassive layer
Courtesy ofESA Space Environment
& Effects Analysis Section
Maria Grazia Pia, INFN Genova Courtesy ESA Space Environment & Effects Analysis Section
X-Ray Surveys of Planets, Asteroids and Moons
Induced X-ray line emission:indicator of target composition
(~100 m surface layer)
Cosmic rays,jovian electrons
Solar X-rays, e, p
Courtesy SOHO EIT
Geant3.21
ITS3.0, EGS4
Geant4
C, N, O line emissions included
low energy e/ extensionswere triggered by astrophysics requirements
Maria Grazia Pia, INFN Genova
……the first user applicationthe first user application
R. Taschereau, R. Roy, J. PouliotCentre Hospitalier Universitaire de Quebec, Dept. de radio-oncologie, CanadaUniv. Laval, Dept. de Physique, CanadaUniv. of California, San Francisco, Dept. of Radiation Oncology, USA
Distance away from seed
RB
E
0 1 2 3 4 5
1
1.02
1.04
1.06
1.08
Mo- Y
M200
-- healthy tissues++ tumors
Goal: improve the biological effectiveness of titanium encapsulated 125I sources in permanent prostate implants by exploiting X-ray fluorescence
Titanium shell (50 µm)
Silver core (250 µm)
4.5 mm
Maria Grazia Pia, INFN Genova
...back to ...back to HEPHEP
Similar requirements on low energy physics from underground experiments
Recent interest on these physics models from LHC for precision detector simulation
Gran Sasso Laboratory
Credit: O. Cremonesi, INFN Milano
Courtesy H. Araujo and A. Howard, IC London
ZEPLIN III
Maria Grazia Pia, INFN Genova
together with...
Medical/Healthcare imaging, diagnosis and treatment
Bioinformatics study of the human genome and proteome to understand genetic diseases
Nanotechnology design of new materials from the molecular scale
Engineering design optimization, simulation, failure analysis and remote Instrument access and control
Natural Resources and the Environment weather forecasting, earth observation, modeling and prediction of complex systems, earthquake
LCG
Maria Grazia Pia, INFN Genova
The response
Technology
Rigorous software engineering
Collaboration
Maria Grazia Pia, INFN Genova
OO technologyOO technology
The “big revolution” in HEP software in the last ~10 years– change of paradigmchange of paradigm, not just moving to a new programming technique
What did we gain?– Openness to changeOpenness to change and stabilitystability– RobustnessRobustness and flexibilityflexibility for alternative implementations– MaintainabilityMaintainability over a long time-scale – Easy integrationintegration of distributeddistributed development
...but the “revolution” has not been fully digested yet– learninglearning a new complexcomplex technology takes time– un-learningun-learning old-fashioned procedural programming is even more difficult
New emerging technologies– Generic Programming, Generative Programming, Aspect Oriented Programming...
Maria Grazia Pia, INFN Genova
Open ScientistOpen Scientist (C++)(C++)
JASJAS (Java)(Java)
AnapheAnaphe (C++)(C++)
AIDAAIDAAbstract Interfaces for Data Analysis
User codeUser code
ROOTROOT,...,... (...)
AAIIDDAA
User Code uses only interfaceinterface classes
Actual implementationsimplementations are selected at run-time (loading shared libraries)
acro
ss la
ng
ua
ge
lan
gu
ag
e b
ound
ary
Italy USA
choose what best fits your experimental needsfreedom to change your choice, without changing a single line in your codeno risk to introduce a dependency on external systems into your experiment
Maria Grazia Pia, INFN Genova
F. P. Brooks,
“No Silver Bullet - Essence and Accidents of Software Engineering”,IEEE Computer 20(4):10-19, April, 1987
As we look to the horizon of a decade hence, we see no silver bullet. There is no single development, in either technology or in management technique, that by itself promises even one order-of-magnitude improvement in productivity, in reliability, in simplicity. ...Not only are there no silver bullets now in view, the very nature of software makes it unlikely that there will be any - no inventions that will do for software productivity, reliability, and simplicity what electronics, transistors, and large-scale integration did for computer hardware. We cannot expect ever to see twofold gains every two years. ...Although we see no startling breakthroughs - and indeed, I believe such to be inconsistent with the nature of software - many encouraging innovations are under way. A disciplined, consistent effortdisciplined, consistent effort to develop, propagate, and exploit these innovations should indeed yield an order-of-magnitude improvement. There is no royal road, but there is a road.
Maria Grazia Pia, INFN Genova
Software engineering
a disciplinediscipline for software engineering
an incrementalincremental and iterativeiterative
software life-cycle
time (dynamicdynamic aspect of the process)
co
nte
nt
( sta
ticst
atic
asp
ect
of t
he p
roce
ss)
Shift attention from computing technology to software process as the way to achieve quality, lower costs... Quantitative standards
to evaluate software capability maturity: SEI’s CMM, ISO 15504
this is the hardest nut to crack...
Maria Grazia Pia, INFN Genova
Domain decomposition
hierarchical structure of
sub-domains
Geant4 architecture
Uni-directional flow of
dependencies
Software EngineeringSoftware Engineering
User requirements– formally collected (PSS-05)
Iterative and incremental software process
– monitored according to ISO 15504
OOAD– architecture and detailed design
Quality assurance– procedures and dedicated testing team
Use of standards– de jure and de facto
Maria Grazia Pia, INFN Genova
TransparencyTransparency
“It was noted that experiments have requirements for independent, alternativeindependent, alternative physics models. In Geant4Geant4 these models, differently from the concept of packages, allow the user to understandunderstand how the results are produced, and hence improve the physics validationphysics validation. Geant4 is developed with a modular architecture and is the ideal framework where existing
components are integrated and new models continue to be developed.” (LCB, 21/10/1997)
Transparency:physics exposed through OO design
Maria Grazia Pia, INFN Genova
CMS muon system
A few examples of Geant4 usage…
9.2 9.40.3 0.40.2 0.5 9 9.6
data data
GEANT3GEANT3
GEANT4GEANT4
high energy limit %
EMB Electron Energy Resolution
stochastic term
%× GeV
Atlas, courtesy of P. Loch
ATLAS HEC
courtesy J.P. Wellisch
legacy FORTRAN
Geant4
data
BaBarBorexino
BaBar: Simulation is robust and reasonably fast1.5 billion production events so far
Maria Grazia Pia, INFN Genova
Geant4 CollaborationGeant4 Collaboration
CERN, ESA, KEK, SLAC, TRIUMF, TJNL
INFN, IN2P3, PPARCBarcelona Univ., Budker Inst., Frankfurt Univ.,
Karolinska Inst., Helsinki Univ., Lebedev Inst., LIP, Northeastern Univ. etc.
MoU basedDistribution, Development and User Support of Geant4
Maria Grazia Pia, INFN Genova
Globalisation
Sharing resources across the world
Maria Grazia Pia, INFN Genova
Wave of interest in grid technology as a basis for “revolution” in e-Science and e-Commerce
An infrastructure and standard interfaces capable of providing transparent access to geographically
distributed computing power and storage space in a uniform way
Ian Foster and Carl Kesselman's book:
”A computational Grid is a hardware and software infrastructure that provides dependable, consistent,
pervasive and inexpensive access to high-end computational capabilities”".
What is the Grid?What is the Grid?“What exactly it is, can not been told …”
Maria Grazia Pia, INFN Genova
What is the Grid?
Resource SharingResource Sharing– On a global scale
Secure AccessSecure Access– Needs a high level of trust
Resource UseResource Use– Load balancing for efficiency
The “Death of Distance”The “Death of Distance”– Requires excellent networking
Open StandardsOpen Standards– Allow constructive distributed
development
Not a single Grid (yet?) ...and many more just in HEP
5.44 GbpsCERN
Caltech
Maria Grazia Pia, INFN Genova
The LHC Computing Grid Project - The LHC Computing Grid Project - LCGLCG
CollaborationCollaborationLHC ExperimentsGrid projects: Europe, USRegional & national centres
ChoicesChoicesAdopt Grid technologyGo for a “Tier” hierarchyUse Intel CPUs in standard PCsUse LINUX operating system
GoalGoalPrepare and deploy the computing environment to help the experiments analyse the data from the LHC detectors
grid for a physicsstudy group
Tier3physicsdepartm
ent
Desktop
Germany
Tier 1
USAUK
France
Italy
Taipei?
CERN Tier 1
JapanCERN Tier 0Tier2
Lab aUni a
Lab c
Uni n
Lab m
Lab b
Uni bUni y
Uni xgrid for a regional group
grid for a physicsstudy group
Tier3physicsdepartm
ent
Desktop
Germany
Tier 1
USAUK
France
Italy
Taipei?
CERN Tier 1
JapanCERN Tier 0Tier2
Lab a
Uni a
Lab c
Uni n
Lab m
Lab b
Uni bUni y
Uni xgrid for a regional group
Maria Grazia Pia, INFN Genova
Analysis on the Grid
Not planned/organized– On the level of the experiment
Not under single control– Lots of people do it simultaneously
Not predictable in accessing data– Slows down disk access considerably
Need information about the nodes– Validation of nodes
Analysis is I/O intensive, rather than CPU intensive– Instead of moving data to processors, the jobs should be run where the
data is
Analysis is (ideally) ‘interactive’– Fast response times needed from the system
Analysis is not productionAnalysis is not production
Many new challenges
Several groups discussing issues around distributed data analysis and the Grid
Maria Grazia Pia, INFN Genova
Physics and mathematics
New functionalityenabled by the technology
Maria Grazia Pia, INFN Genova
Simulation (Geant4)Experimental data
Energy (keV)
Fluorescent spectrum of Icelandic Basalt (“Mars-like”)
Experimental data: 6.5 keV photon beam, BESSYCourtesy of A. Owens et al., ESA
ESA Bepi Colombo Bepi Colombo mission to Mercury
Analysis of the elemental composition of Mercury crust through X-ray spectroscopy
X-ray fluorescence, PIXE, X-ray fluorescence, PIXE, AugerAuger
electromagnetic physics down to ~ 100 electromagnetic physics down to ~ 100 eVeV
many more new features,no time to mention them all...
Maria Grazia Pia, INFN Genova
Detector monitoringDetector monitoring
SimulationSimulation vs. experimental datadata
Data reconstructionreconstruction vs. expectationsexpectations
Physics analysisPhysics analysis– comparisons of experimental distributions
(ATLAS vs. CMS Higgs)– comparison with theoretical distributions
(data vs. Standard Model)
Regression testing– throughout the software life-cycle
Statistics Statistics for Data Analysis
Goodness-of-fit testsGoodness-of-fit testsPearson’s Pearson’s 22 test
KolmogorovKolmogorov test
Kolmogorov – SmirnovKolmogorov – Smirnov test
GoodmanGoodman approximation of KS test
LillieforsLilliefors test
KuiperKuiper test
Cramer-von MisesCramer-von Mises test
Fisz-Cramer-von MisesFisz-Cramer-von Mises test
Anderson-DarlingAnderson-Darling test
Goodness-of-fit testsGoodness-of-fit testsPearson’s Pearson’s 22 test
KolmogorovKolmogorov test
Kolmogorov – SmirnovKolmogorov – Smirnov test
GoodmanGoodman approximation of KS test
LillieforsLilliefors test
KuiperKuiper test
Cramer-von MisesCramer-von Mises test
Fisz-Cramer-von MisesFisz-Cramer-von Mises test
Anderson-DarlingAnderson-Darling test
Anderson-DarlingAc (95%) =0.752
Maria Grazia Pia, INFN Genova
The impact on society
Technology transfer from HEP
Maria Grazia Pia, INFN Genova
Technology transfer
Particle physics software Particle physics software aids space and medicineaids space and medicine
“Geant4 is a
showcase example of technology transfer from particle
physics to other fields such as space and medical science”
June 2002
http://www.cerncourier.com...and vice-versa: valuable feedback and
contribution to validation from non-HEP fields
Maria Grazia Pia, INFN Genova
Develop a Develop a general purposegeneral purpose
precise precise dosimetric system
with the capability of
realistic geometryrealistic geometryand material modelingand material modeling
interface to CT imagesinterface to CT images
with a user-friendly interfaceuser-friendly interface
atat low costlow cost
adequate adequate speedspeed for clinical usage for clinical usageperforming atperforming at
The challenge (dream...)
Maria Grazia Pia, INFN Genova
Precise physics
Accurate geometry and material modelling
Generality through OO technology
Friendly interface through the web
Speed through parallelisation and access to distributed resources
Analysis tools for dosimetry
-40 -30 -20 -10 0 10 20 30 400,0
0,5
1,0
1,5
2,0
2,5 Simulazioni Plato
Dose %
Distanza lungo Z (mm)
Distance along Z (mm)
Effects of source
anisotropySimulationSimulationPlatoPlato
AIDA + Anaphe
Any hospital
– even small ones, or in less wealthy countries, that cannot even small ones, or in less wealthy countries, that cannot afford expensive commercial software systemsafford expensive commercial software systems –
may have access to advanced software technologies and tools for radiotherapy
Maria Grazia Pia, INFN Genova
archeoGRIDarcheoGRID
Maria Grazia Pia, INFN Genova
Meditations...Unprecedented challenges
– complexity of physics and detectors
A fast-changing computing environment– long time scale of the experiments’ life-cycle
Globalisation & collaboration: a worldwide effort– common needs, common resources
New technologies play an essential role to cope with the complexity– but rigorous software engineering is as essential as technology
Software is as essential as hardware in our experiments– and requires a large investment of resources
– LHC offline software and computing investments exceed the cost LHC offline software and computing investments exceed the cost of a LHC experiment like ATLAS or CMS!of a LHC experiment like ATLAS or CMS!
Maria Grazia Pia, INFN Genova
We must be still and still movingInto another intensityFor a further union, a deeper communion ...In my end is my beginning.
Four Quartets – East CokerThomas S. Eliot, 1940
In my beginning is my end.