Comments (3)
Posit arithmetic is actually emulated using (un)signed integers. So on every operation a 16-bit posit is disassembled into its different bits (sign, regime, exp and fraction) and then afterwards they are concatenated again. But its slow, yes 😄
For SpeedyWeather.jl to run in 16-bit posits there are currently two bottlenecks
- a type-flexible fourier transform (everything else is type flexible at the moment), see #31
- (a much bigger bottleneck) rewriting the precision-critical algorithms for low precision. At the moment everything works fine in Float32, but lower precision will likely fail. So tricks like scaling, reordering, compensation have to be further build in.
from speedyweather.jl.
See also milankl/SoftPosit.jl#64
from speedyweather.jl.
closed in favour of #137
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Related Issues (20)
- Precompilation Error HOT 2
- Add proper citations in Docs via DocumenterCitations.jl HOT 1
- JOSS review: text comments HOT 6
- Replace `PythonPlot` with a Julia-based plotting library in Docs HOT 2
- Verifying conserved quantities HOT 15
- Modified dynamics HOT 16
- PrimitiveDry and WetModel generation on Julia v1.9 hangs HOT 10
- The PrimitiveWetModel example fails HOT 10
- unbalanced initial condition for Galewsky Jet HOT 4
- ShallowWater dataset on PDEArena HOT 6
- Modularise netCDF output
- Time stepping of particle tracking HOT 1
- Virtual temperature as prognostic variable
- Spectral filtering instead of hyperdiffusion
- Lagrangian sampling of the model state HOT 1
- Instability develops over long integrations HOT 24
- set! initial conditions HOT 2
- Additional LowerTriangularArray functionality HOT 11
- arbitrary tracer support HOT 2
- RingGrids: Conflicting Broadcast Rules HOT 2
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