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vectorization in firedrake
tj-sun edited this page Jan 19, 2019
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Install with the script in the tsfc2loopy
branch of firedrake with the arguments
--package-branch firedrake tsfc2loopy --package-branch tsfc tsfc2loopy --package-branch PyOP2 siam-vec --package-branch loopy cvec
- Start from a normal firedrake installation
- Check out the branches:
- firedrake: tsfc2loopy
- tsfc: tsfc2loopy
- PyOP2: siam-vec
git clone https://github.com/firedrakeproject/loopy --recursive
- Install loopy with e.g.
pip install -e loopy/
- Check out loopy branch cvec
To reduce the complexity and chances of surprises, I've cut corners in a few places:
- Vectorization is off by default, this means on these branches, we are just running as if on the pull request #1186. Turn on vectorization manually by setting PyOP2 parameters:
from firedrake import parameters
parameters['pyop2_options']['simd_width'] = 4
- OpenMP backend is removed, i.e. vectorization is only through vector extensions and no OpenMP pragmas.
- Reminder loop generation needs more work with vector extensions, so that is removed for now. This means the demo will only work if the number of elements is multiple of batch size.
- Vectorization is switched off for matrix assembly.
Building locally
Tips
- Running Firedrake tests with different subpackage branches
- Modifying and Rebuilding PETSc and petsc4py
- Vectorisation
- Debugging C kernels with
lldb
on MacOS - Parallel MPI Debugging with
tmux-mpi
,pdb
andgdb
- Parallel MPI Debugging with VSCode and
debugpy
- Modifying generated code
- Kernel profiling with LIKWID
- breakpoint() builtin not working
- Debugging pytest with multiple processing
Developers Notes
- Upcoming meeting 2024-08-21
- 2024-08-07
- 2024-07-24
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