Comments (2)
How did you measure that? For me, with beta1:
julia> @time m=[big(1)//(n+m) for n in 1:35, m in 1:35]; m*inv(m);
0.159363 seconds (270.70 k allocations: 13.532 MiB, 16.09% gc time, 93.20% compilation time)
julia> @time m=[big(1)//(n+m) for n in 1:35, m in 1:35]; m*inv(m);
0.042357 seconds (74.48 k allocations: 3.597 MiB, 98.83% compilation time)
and with beta2
julia> @time m=[big(1)//(n+m) for n in 1:35, m in 1:35]; m*inv(m);
0.149622 seconds (271.06 k allocations: 13.540 MiB, 14.87% gc time, 92.18% compilation time)
julia> @time m=[big(1)//(n+m) for n in 1:35, m in 1:35]; m*inv(m);
0.040999 seconds (74.47 k allocations: 3.595 MiB, 98.85% compilation time)
julia> versioninfo()
Julia Version 1.11.0-beta2
Commit edb3c92d6a6 (2024-05-29 09:37 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 8 × Intel(R) Core(TM) i7-4870HQ CPU @ 2.50GHz
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, haswell)
Threads: 1 default, 0 interactive, 1 GC (on 8 virtual cores)
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I was using @b from Chairmarks. But I cannot reproduce with @time. Sorry for the wrong message. I close the issue
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