Hello, I am a newcommer in Julia. I have read almost entire never ending boring manual, read a couple books, watched some videos, and practicing probability theory with julia with much enthusiasm. I spend great of time to understand the type system and parametric types. But the more I get into the…

[image] Jean_Michel: when I need BigInt in a mathematical computation, usually only a few of the numbers involved are too big for Int What I meant is that if you are running a single piece of code multitple times and that line of code either needs or not need BigInt, then that line of code wi…

[image] yuyichao: Of course it’s entirely possible that only a small portion of your code needs BigInt and you should limit your use of BigInt to those few lines of code Normally, big numbers appears in divisions (by another big number) so an alternative approach would be to contain those div…

This is not the way it goes. A typical example I had recently is when compute the size of a set, about 10^9 intermediate computations did fit with in Int64 or Int128 and only about 30 did not fit. I have the choice to redo entirely the computation in BigInt (very slow) or (better) to use SaferIntege…

So you are saying you repeated the computation 10^9 times?

[image] Jean_Michel: have the choice to redo entirely the computation in BigInt (very slow) or (better) to use SaferIntegers Maybe try BitIntegers.jl, they work well for me, much faster than bigints [image] ANN: BitIntegers.jl (Int256, ...) and BitFloats.jl (Float80, Float128…

No. I said that the computation demanded 10^9 intermediate computations, which were all different, and that about 30 of them overflowed Int128. And that this is fairly typical of the kind of computations that I have to do in representation theory of Hecke algebras, one of my topics.

I did a quick test of Int256. In this test it is slower that BigInt, probably because of divisions… function test_hm(rtype,rank) hm(rank)=[rtype(1)//(n+m) for n in 1:rank, m in 1:rank] m=hm(rank) one(m)==m*inv(m) end julia> @btime test_hm(Int256,45) 3.213 s (56720623 allocations: 1.12 GiB) …

And that’s not what I was saying. 30 out of 10^9 doesn’t matter. The question is how many expressions in your code overflows. Only repeated calculation that can overflow matters.

Well, actually, it is a single one (complicated) expression which overflows (about 30 times in 10^9). The values of the variables in the expression are different each time and I cannot predict which values will make the expression overflow.

Tonight I hated julia, REPL and overflows

New to Julia

Jakub_Wronowski February 22, 2020, 11:13pm 39

Maybe try BitIntegers.jl, they work well for me, much faster than bigints

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Tonight I hated julia, REPL and overflows

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