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Minimally invasive GPU implementation with KernelAbstractions.jl without neighborhood search #493
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #493 +/- ##
==========================================
- Coverage 69.42% 68.40% -1.03%
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Files 69 69
Lines 3967 4038 +71
==========================================
+ Hits 2754 2762 +8
- Misses 1213 1276 +63
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Fix doc strings. |
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Superseded by #534. |
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See #484.
Based on #532 and #533.
This PR is working only with KernelAbstractions.jl, without even using CUDA.jl in TrixiParticles or in an extension module.
All you have to do to run the
dam_break_2d.jl
example on an NVidia GPU is the following:semidiscretize
call in the file toode = semidiscretize(semi, tspan, data_type=nothing)
. This doesn't do anything, asdata_type=nothing
is the default, but it allows us to overwrite it withtrixi_include
. Note that I didn't add this to the file because this feature is experimental and not (yet) documented.Semidiscretization
call in the file tosemi = Semidiscretization(fluid_system, boundary_system, neighborhood_search=nothing)
, since neighborhood search is not yet supported.data_type=CuArray
to run this on the GPU with CUDA.jl. We can also passdata_type=nothing
(the default), which runs the usual code with Polyester.jl. And we can passdata_type=Array
to run the GPU kernels compiled by KernelAbstractions.jl on the CPU. We could also passdata_type=ROCArray
to run a simulation on an AMD GPU.