UQLab 2.0 and UQCloud: open-source vs. cloud-based uncertainty quantification - Research Collection
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ETH Library UQLab 2.0 and UQCloud: open- source vs. cloud-based uncertainty quantification Other Conference Item Author(s): Lataniotis, Christos ; Marelli, Stefano ; Sudret, Bruno Publication date: 2022-04-14 Permanent link: https://doi.org/10.3929/ethz-b-000544670 Rights / license: Creative Commons Attribution 4.0 International This page was generated automatically upon download from the ETH Zurich Research Collection. For more information, please consult the Terms of use.
UQL AB 2.0 and UQC LOUD: Open-Source Vs. Cloud-Based Uncertainty
Quantification
SIAM UQ 2022, April 13 2022
C. Lataniotis, S. Marelli, B. Sudret
Chair of Risk, Safety and Uncertainty Quantification
SIAM UQ 2022
How to cite?
This presentation was given at the SIAM UQ2022 Conference, Atlanta, April 14, 2022 (online).
How to cite
Lataniotis, C., Marelli, S. and Sudret, B. UQL AB 2.0 and UQC LOUD: Open-Source Vs. Cloud-Based Uncertainty
Quantification, SIAM Conf. on Uncertainty Quantification, Atlanta, GA (USA), April 12-15.
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 1 / 17
A few words about the UQL AB project
Our mission: Make uncertainty quantification available for anybody, in any field of applied
science and engineering
Our goals:
• Disseminate a general purpose,
non-intrusive, black-box UQ mindset
• Provide a software to quickly deploy it
• Appeal to both academia and industry
• Address an audience of non-specialists
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 2 / 17
The UQLab ecosystem
UQL AB UQW ORLD
• General purpose software for UQ • Open to anyone (not just UQL AB users!)
• Close to 4,500 users from 90+ countries • Plenty of topics
• Over 100,000 lines of code • Hundreds of registered users
• Written in M ATLAB • User-to-user interactions
www.uqlab.com www.uqworld.org
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 3 / 17
A quick look at the UQL AB software in 2021
Original goals: Status in 2021:
• Highly modular, seamlessly integrated design 19 integrated modules
• Very fast learning curve for non-specialists Used in ∼600 scientific works
• Unique documentation model Hundreds of citations
• Open source scientific algorithms BSD 3-clause license only on the modules
• Portability on windows/linux/mac systems M ATLAB-based
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 4 / 17
A mixed licensing model
Rationale: all the scientific content needs to be publicly available, but its commercial exploitation should support the
development of the software
Our solution (2017–2021): two separate software packages1
UQLabCore UQLabModules
• A domain specific language (DSL) made for UQ • A collection of algorithms for UQ (probabilistic
• Handles bookkeeping, memory, updating, modelling, surrogate models, reliability analysis, etc)
content-management, etc • Extensive documentation
• Contains no science/algorithms • Open source (BSD 3-clause license)
• Handles user licenses • Can be modified and extended by the user
• Closed source, requires registration • Requires UQLabCore to be used out-of-the-box
Free for academic users, non-free licensing options available for commercial/private use
1
https://uqworld.org/t/why-a-licensing-system-is-uqlab-really-open-source/143
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 5 / 17
Almost 5 years after: did it work?
The good... ...the bad
• Thousands of unique users from Academia • Requires maintenance of a complex licensing
high-availability backend infrastructure
• Highly cited manuals
• Requires live internet connectivity during startup
• Lots of collaborations started with groups worldwide
• Requires a valid M ATLAB license ($$$!)
• Contributed to widespread adoption of many niche
UQ tools in applied research, such as PCE and active • Perceived as closed-source due to obscured
learning-based reliability UQLabCore code
...and the ugly
• Commercial licensing extremely complex and time-consuming
• Very little commercial interest for general-purpose UQ software
So... what now??
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 6 / 17
UQL AB 2.0
We went fully open source!
• Released Feb. 1st, 2022
• UQLabCore and UQLabModules are now merged in
the single UQL AB software
• No more internet connectivity required
• All licensing code stripped from the core (now also
open-source)
• BSD 3-clause license: commercial exploitation now
allowed for everyone, with attribution
• Registration still required, but automatic and open to
everyone (only used to communicate with the
userbase)
Go ahead and try it out now!
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 7 / 17Ok but why M ATLAB then2
Our requirements back in 2013
• Interpreted language (no compilation)
• High-level pre-existing objects and built-in functions
• Mature environment for easy install
• Well-known in academia AND in the industry
• Designed for scientific programming
Pros Cons
• Quick learning curve • Paying licenses (expensive for industry)
• Standard in academia and industry, well supported • High-level libraries not part of basic M ATLAB
• Object-oriented and fast (toolboxes)
• Portable (Win, MacOS, Linux) • Perceived as not-open-source
• Powerful debugging-profiling
2
https://uqworld.org/t/matlab-but-but-python-r-c-cobol/147
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 8 / 17And in 2021 ?
Some limitations
• Standalone, local software is “old style”, gradually disappearing
• M ATLAB is not the ideal language for machine learning, integration is limited
• Different communities and companies use different toolkits, languages and tech stacks
How can we work around these without rewriting UQL AB in python, R, Julia, etc. ?
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 9 / 17Let’s put it in the cloud! – The UQC LOUD project
Introducing UQC LOUD
• Platform-independent SaaS
• Matlab-based, following the UQLab roadmap
• Deployed on a modern, scalable cloud-based infrastructure
• Platform- and language- independent
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 10 / 17The UQC LOUD architecture
UQC LOUD is a Software-as-a-Service (SaaS) solution for UQ computations powered by UQL AB
• UQC LOUD provides a secure REST API service that handles
JSON requests and produces JSON responses
• Software bindings
– Open source wrapper software for different languages
– Distributed on standard repositories (PyPI, CRAN, Julia...)
– Only O(102 ) lines of code vs O(105 ) of the full UQL AB
source
– Provide similar user experience to UQL AB
Advantages
• No Matlab license needed
• Continuous integration with UQL AB
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 11 / 17UQLab vs. UQCloud
UQCloud goal: provide on-demand UQLab computations via API calls
UQL AB UQC LOUD
• Installed by user on their machine • UQLab is pre-"installed" on the cloud
• User-defined models (e.g. FEM) can be • UQCloud covers most of the computational
connected in a straightforward manner (UQ cost
MODEL, UQLink) • UQCloud must "remember" the previous
• User covers the computational cost calls made by the user (stateful API)
• Running a UQLab session per user is • Sanity requirement: users run their
almost trivial computational models locally
• Matlab license fees covered by the user • No Matlab fees for users!
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 12 / 17First set of bindings: UQ[py]Lab!!
Coming [very] soon
• Fully functional python-bindings for UQC LOUD
• Beta testing phase almost complete
• Finalizing and documenting production version
• Release 1.0 expected Summer 2022
• Public free instance available to all academic users
(with some load limitations)
Beta registrations are still open for a short time! https://uqpylab.uq-cloud.io
Volunteers welcome to write R / Julia / C++ bindings !
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 13 / 17UQ[Py]Lab in a notebook
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 14 / 17See it in action: reliability analysis of a truss structure in Matlab and python
Truss structure: UQLab (Matlab) code: UQ[py]Lab (Python) code:
InputOpts . Marginals (1) . Name = ' E1 '; InputOpts = {
InputOpts . Marginals (1) . Type = ' ' Marginals ' : [
Lognormal '; { ' Name ' : ' E1 ' ,
InputOpts . Marginals (1) . Moments = [2.1 ' Type ' : ' Lognormal ' ,
e11 , 2.1 e10 ]; ' Moments ': [2.1 e11 , 2.1 e10 ]} ,
InputOpts . Marginals (2) . Name = ' E2 '; { ' Name ' : ' E2 ' ,
... ...
]}
myInput = uq_cr eateInpu t ( InputOpts ) myInput = uq . createInput ( InputOpts )
Parameter distributions: ModelOpts . mFile = ' truss_model '; ModelOpts = {
' Type ': ' Model ' ,
Name Type µ σ/µ ' ModelFun ': ' truss . model '
}
E1 ,E2 (P a) Lognormal 2.1 × 1011 10%
myModel = uq_cr eateMode l ( ModelOpts ) ; myModel = uq . createModel ( ModelOpts )
A1 (m2 ) Lognormal 2.0 × 10−3 10%
2 −3
A2 (m ) Lognormal 1.0 × 10 10% AnalysisOpts . Type = ' Reliability '; AnalysisOpts = {
P1 , . . . , P6 (N ) Gumbel 5.0 × 104 15% AnalysisOpts . LimitState . Threshold = ' Type ' : ' Reliability ' ,
0.13; ' LimitState ':
AnalysisOpts . Method = ' IS '; { ' Threshold ': 0.13 } ,
AnalysisOpts . MaxSamples = 1 e4 ; ' Method ': ' IS ' ,
Matlab-Python workflow comparison: ' MaxSamples ': 1 e4
}
https://youtu.be/2Q_6zxtj7O0 myAnalysis = u q _ c r e a t e A n a l y s i s ( myAnalysis = uq . createAn alysis (
AnalysisOpts ) AnalysisOpts )
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 15 / 17Active learning on the 2D hat function
g(x1 , x2 ) = 20 − (x1 − x2 )2 − 8 (x1 + x2 − 4)3 Xi ∼ N (0.25, 1) , i = 1, 2 Under the hood:
InputOpts = { uq . print ( AKMCSAnalysis )
" Marginals " : [
{ " Name " : " R " ,
" Type " : " Gaussian " ,
" Moments " : [5.0 , 0.8]} ,
{ " Name " : " S " ,
" Type " : " Gaussian " ,
" Moments " : [2.0 , 0.6]}
]}
myInput = uq . createInput ( InputOpts )
ModelOpts = { ' Type ': ' Model ' ,
' ModelFun ': ' Hat . model '} uq . display ( AKMCSAnalysis )
myModel = uq . createModel ( ModelOpts ) Features
AKMCSOpts = { • Full bi-directional communication
" Type " : " Reliability " ,
" Method " : " AKMCS " • Model evaluations are executed locally
}
AKMCSAnalysis = uq . crea teAnaly sis (
• Minimal communications
AKMCSOpts )
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 16 / 17Summary & Outlook
Summary
• UQL AB has been a successful project, yet with some limitations
• Version 2.0 is now fully open-source to feed both industrial and private users’ needs
• To tap into different communities that use different languages/tech stacks, we introduced the UQCloud project
• We gave a brief demonstration/example of UQ[Py]lab, the first set of software bindings, that allows full access to the
functionality within the python language
• Release of UQ[py]Lab 1.0 in Summer 2022!
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 17 / 17Questions ?
The Uncertainty Quantification
Software
www.uqlab.com
The Uncertainty Quantification
Community
www.uqworld.org
Chair of Risk, Safety & Uncertainty Quantification
www.rsuq.ethz.ch
UQ in the cloud SIAM UQ 2022 C. Lataniotis, S. Marelli, B. Sudret 17 / 17You can also read
