computational geosciences at uni. oxford …...seismology oceanography computational geosciences at...

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Geodynamics

Seismology

Oceanography

Computational Geosciences at Uni. Oxford Dave A May Department of Earth Sciences [email protected]

mailto:[email protected]

Cambridge Scientific Computation Day, March 20, 2017

Computational geoscience: An example

Domain ~ O(109) km3

• 20M year time scale (5000 time steps)

• O(108) DOFs

• 8k cores

Figure from: https://www.studyblue.com/notes/note/n/test-1/deck/3631502

Geodynamics: Addresses fundamental questions related to the origin and evolution of the planetary interiors, e.g.

why does Earth have tectonics? how does topography encode the deformation history?



Domain ~ O(109) km3


• O(108) DOFs

• 8k cores Rudi et al, “An Extreme-Scale Implicit Solver for Complex PDEs: Highly Heterogeneous Flow in Earth’s Mantle”, SC’15

⌦


Global scale models • highly viscous flow + conservation of energy• non-linear viscosity• domain: entire mantle O(1012) km3• 1B year time scale (106 time steps)• O(1013) DOFs• 1.5M cores —> 12 hrs per Newton solve per

time step• Gordon Bell winner 2015





Domain ~ O(109) km3


• O(108) DOFs

• 8k cores

May et al, “pTatin3d: High-performance Methods for Long-Term Lithospheric Dynamics”, SC’14

⌦


Regional scale models • multiple materials, topography, large

deformation• Drucker-Prager plasticity• domain: O(109) km3• 20M year time scale (104 time steps)• O(108) DOFs• 8k cores —> 20 hrs per simulation

Global scale models • highly viscous flow + conservation of energy• non-linear viscosity• domain: entire mantle O(1012) km3• 1B year time scale (106 time steps)• O(1013) DOFs• 1.5M cores —> 12 hrs per Newton solve per

time step• Gordon Bell winner 2015




Oxford Earth science dept. dichotomy

Experimental based research groups• geochemistry; petrology; planetary materials; rheology• 17 faculty members• 4 labs (cosmotope; exp. petrology; noble lab; rock rheology) • 5 full-time technicians • 4 full-time lab managers

Computation based research groups• geodynamics; geodesy; seismology; oceanography• 7 faculty members• 0 in-house computational labs • 0 CS&E research staff (part-time or full-time)


Typical software cycle

Typical E.-Sci. PhD (or post-doc) commences with little training in computational math, programming, numerics and software development

They proceed to develop a “hero” code

• progress is slow and painful due to limited experience developing software

• single author, single user

• solves a specific problem (their research topic) … however …

- no documentation (usually);

- no capacity for reproducible tests (maybe no tests);

- not portable;

- non extensible (probably);

- upon graduation / departure, support for that code is reduced, or completely halted;


Typical software cycle

Consequences • Extension of the software to address new research questions are

difficult

(i) a follow-up student loses time trying to make the inherited hero code solve their new problem;

(ii) they give up, and write their own tool — another hero code is born;

(iii) they graduate, the pattern repeats;

Research groups periodically lose in-house modelling expertise and modelling capabilities

Continuity of research themes is often difficult / impossible

Community codes partially resolve this dilemma, however (i) expertise is not in-house; (ii) a community code does not exist for all fields in geoscience


Realities

Developing code / software to obtain solutions to complex problems is different today, cf. 20 years ago

➡ The concept of open source software has been established➡ Good open source libraries are in abundance➡ Leveraging existing packages leads to rapid development, more time doing

science, less time re-inventing the wheel➡ Developing, enhancing, distributing high quality computational software is a

specialist task beyond what can be expected of a geophysics faculty member ➡ The days of the hero code are over

Computation forms a crucial and complementary component of many geoscience domains

Departmental perspectives need to be changed to support cutting-edge computational geoscience research The dichotomy needs to be eradicated … but how?


SRF in computational geosciences

Generate departmental support to create a CS&E position

Convince the HoD of the realities

Job description • contract type: on-going• non-faculty position (departmental hire, no college affiliation)• ability to support groups with alg. dev., software dev., HPC, pump priming• ability to support management of groups specific computing requirements• ability to obtain external funds through own grants, or by boot-strapping onto

dept. grants• must conduct independent research• must be REF-able• no explicit teaching commitments

Convince the university to open the position


SRF services

Lead the development of new research software driven by application science using modern numerical methods, modern software practices and leveraging existing libraries*

Development of efficient PDE solvers

HPC expertise

Advice concerning suitable discretisations for a given PDE

Advice concerning best practices for software design, software development and software management and maintenance

Code reviews and assistance with re-designing, re-factoring and support for re-writing existing in-house software

On-demand training related to any aspects of CS&E


Primary objectives

Knowledge transferal concerning best practices in software design and software development, starting with:

• Push (forcefully) groups to use version control software

• Consolidate all new and existing group software into GitHub or BitBucket

• Push groups to adopt continuous integration*

Development and distribution of shared (open-source), re-usable in-house software tools for computational geoscience research

Open new frontiers of scientific research to department members (and the broader geoscience community). Enable computations that were assumed, or deemed to be, algorithmically or computationally intractable


On-going projects

Geodynamics

• Software realisation of efficient algorithms, discretizatons, and solvers for two-phase flow in geodynamic scenarios

Seismology

• Spectral FE for wave propagation on tetrahedral meshes

• Hybrid methods coupling local and global methods

Oceanography

• Forward model agnostic Lagrangian analysis tools

computational geosciences at uni. oxford …...seismology oceanography computational geosciences at...

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