Arithmetic operations are not performed #66
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bug
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I'd have to debug it a bit and don't really have the time now, but this is likely an upstream bug in https://gitlab.com/cerlane/SoftPosit, since the operation you're doing is SoftPosit.jl/src/arithmetic.jl Line 3 in aa307d5 |
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Thanks Mosè for looking into this. Indeed, while I've been trying to replace piece by piece of C-SoftPosit with pure Julia implementations, all arithmetic operations are still using a ccall. Alexandros, could you run the unit tests on your M1 with #main by doing julia>] test SoftPositand post the test summaries here? |
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Thank you very much, indeed, @giordano. |
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@alexandrosstamatiou could you please quote all your code blocks with triple backquotes? That'd make reading these long blocks much easier. Thanks. |
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Sorry - is this what you meant? |
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Yup, it looks much better 🙂 Thanks! |
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As we thought, the problem is not the Julia code but the C code. In the Posit16(x) == Posit16_old(x) the first function calls a conversion that I’ve written in Julia to replace the C version and Posit16_old calls C SoftPosit. However that also means you could, for the time being, redefine all arithmetic operations via back&forth conversion. Like so
```
Base.:(+)(x::Posit16,y::Posit16) = Posit16(Float32(x)+Float32(y))
```
… On 11 May 2022, at 19:33, Mosè Giordano ***@***.***> wrote:
Yup, it looks much better 🙂 Thanks!
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At the moment, defining the arithmetic operations as conversions with Float32 is even faster julia> using SoftPosit, BenchmarkTools
julia> A,B = Posit16.(rand(1000,1000)),Posit16.(rand(1000,1000));
julia> @btime +($A,$B);
25.558 ms (2 allocations: 1.91 MiB)
julia> Base.:(+)(x::Posit16,y::Posit16) = Posit16(Float32(x)+Float32(y))
julia> @btime +($A,$B);
18.911 ms (2 allocations: 1.91 MiB)Probably because I tried to squeeze some performance out of the Posit16-Float32 conversion in Julia in #55 but |
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Also meaning that I'd be happy to accept a PR that replaces ccall-arithmetic operations by pure Julia ones (whether via conversion or if anyone wants to write a posit addition from scratch, feel free 😄 ) |
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upcoming v0.5 will be independent of C-SoftPosit. I overhauled the conversions and all arithmetics now use those to instead of calling specific posit-arithmetic functions. At the moment this is, despite the detour via float arithmetic, even faster than C-SoftPosit and the conversions are much faster (see #69). Feel free to report here whether #68 (branch |
julia> using SoftPosit
julia> a = Posit16(1.0);
julia> a + a
Posit16(2.0)
julia> versioninfo()
Julia Version 1.9.0-DEV.732
Commit ada860fe7d* (2022-06-10 15:07 UTC)
Platform Info:
OS: macOS (arm64-apple-darwin21.5.0)
CPU: 8 × Apple M1
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-13.0.1 (ORCJIT, apple-m1)
Threads: 4 on 4 virtual cores
julia> pkgversion(SoftPosit)
v"0.5.0" |
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Given that SoftPosit.jl v0.5 seems to work on M1, I'm closing this. |
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Hi again,
I'm sorry, but there is another issue which I thought to mention in a different post. After resolving the method errors following your suggestions in the previous Issue post, the computation ran but wouldn't terminate! Many potential reasons of course, but I discovered that simple arithmetic operations of
Posit16values don't work on my Mac (M1 processor):julia> a = Posit16(1.0);julia> a + aPosit16(1.0)The same lines on the Windows machine give
julia> a = Posit16(1.0);julia> a + aPosit16(2.0)Any ideas why this would happen? Recall that I installed the via Main to get SoftPosit.jl working on the Mac...
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