Track 4 (WFA): WFA, WSE Field-equation API¶
Field equations, includes ML inference.
Good Match Criteria: You would be a good match for this track if your research can integrate and make use of the WFA library.
WFA: API recently used for advancing CFP simulations at unprecedented resolution and speed (more info).
- Pioneering work - Beta testing of the WFA library.
- Only a few groups would be welcomed.
- Close collaboration with Dr. Dirk Van Essendelft's team, PSC, and Cerebras.
- Field equations, includes ML inference
Project Guidelines¶
Problem Requirements¶
- Must lay out on a Hex grid (3d or many 2d parallel)
- Should involve Spatial Locality
- Should be Data Intense
- Single Precision, <40GB
Problem Examples¶
- Computational Fluid Dynamics (FVM, FDM, FEM, LBM)
- Structural Mechanics
- Geomechanics
- Weather/Climate
- Materials – Ising Model, Density Functional Theory
- CNN/RNN inference
Project Requirements¶
- Build a Python class that imports the WFA and contains a “Library” to solve your scientific problem
- Post on a public GitHub
What to expect¶
- Development at the high-level Python interface that is similar to Numpy
- A container (provided by Cerebras) to compile and generate binaries and run on the WSE
- An unpolished product (Beta level) that will require some hand holding from our team on slack
- Be prepared for bugs and unpolished documentation
- Exceptional speed if successful, strong scaling that can’t be matched elsewhere
Please visit the official WFA Documentation for more information.
Track Specific Questions¶
If your project falls under this track, make sure to address the following questions in your application document:
- Can your problem lay out on a Hex grid (3d or many 2d parallel)?
- Does your problem involve Spatial Locality?
- Is your project Data Intense? Please, elaborate.
- Is your problem compatible with single precision and with a total data volume not exceeding 40 GB?
- Which of the following applies to your problem/project? a. Computational Fluid Dynamics (FVM, FDM, FEM, LBM) b. Structural Mechanics c. Geomechanics d. Weather/Climate e. Materials – Ising Model, Density Functional Theory f. CNN/RNN inference
- Are you willing to commit to the following as you advance your project? a. Build a Python class that imports the WFA and contains a “Library” to solve your scientific problem. b. Post on a public GitHub.