On the Infinity of Twin Prime and other K-tuples - Page 6

LaurV · 2020-09-09, 03:53

Quote:

Originally Posted by mart_r

one in Pari... I'm not yet familiar with coding in Perl or C

Man, if you wrote such thing in pari, then you are already "familiar" with C more than you imagine. You can give it a try using either libpari or gwnum, to avoid implementing some things from scratch (but sieving and such, there are a lot of functions and ready-made implementations already). C is extremely simple, only few instructions to learn, haha, it will be the OS you will have to struggle with (like, writing C for Windows or for Linux may be sometimes two different worlds). But you don't know until you try. Give it a try, and there are many guys here who can help you (me included). Just ask.

Perl, on the other hand, is a different animal. It took me some time and effort to learn to deal with regex-es, even after 20 or 30 years of programming experience, and even so, I never wrote more than few scripts in Perl (and I consider myself a very strong programmer in C, many flavors of assembler, Pascal, Fortran, Basic, Lisp). Of course, your mileage may vary, some people here (like Chalsall and DanaJ, who both of them eat Perl on butter every morning for breakfast, I assume) will tell you a different story.

But you have to try first. While you don't buy that lottery ticket, you can't win.

jzakiya · 2020-09-10, 17:54

To test the correctness of your implementation, first search for known large Twins (I assume that's what your looking for) to verify it finds them. Once you know the structure of the program is correct you can use any generator you want, dependent upon the capacity of your hardware to accommodate it.

If you use P23 or P29 you ideally want as many parallel threads as possible. GPUs would be very nice to use in this case, though a Super Computer would be the most ideal platform, more for its memory capacity than just pure speed and threads.

If you are concerned about speed, you need to use a compiled language that has good/mature multi-threading capability, though you can use Perl, etc, to code a proof-of-concept design to get working. All my original coding was done in Ruby, which allowed my to easily and quickly play with different implementations. I then translated that code into Rust, Nim, Crystal, and D multi-threaded versions, and tested their results to Ruby.

First, study my code to know exactly what and why its doing. Then start slow. Know what and why the results should be at each stage of your code for each section. The algorithm is very simple, if you understand it. Once you do, you can run it on any platform in your language(s) of choice.

If you need help post code on git[hub|lab], or a gist, or email me.

jzakiya · 2020-10-24, 14:20

There's a Rust forum post (2020/10/22) about a package to use Rust on GPUs.

https://users.rust-lang.org/t/introd...-gpu-0-1/50499

I don't have a GPU, so I don't have the hardware to play with it.
For those who do, this package should (?) provide the basics to implement the algorithm on GPUs, which (if properly done) increase performance significantly, while extending the number space range too.

https://github.com/EmbarkStudios/rus...eases/tag/v0.1

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2020-09-10, 17:54	#57
jzakiya Jul 2014 100000₂ Posts	To test the correctness of your implementation, first search for known large Twins (I assume that's what your looking for) to verify it finds them. Once you know the structure of the program is correct you can use any generator you want, dependent upon the capacity of your hardware to accommodate it. If you use P23 or P29 you ideally want as many parallel threads as possible. GPUs would be very nice to use in this case, though a Super Computer would be the most ideal platform, more for its memory capacity than just pure speed and threads. If you are concerned about speed, you need to use a compiled language that has good/mature multi-threading capability, though you can use Perl, etc, to code a proof-of-concept design to get working. All my original coding was done in Ruby, which allowed my to easily and quickly play with different implementations. I then translated that code into Rust, Nim, Crystal, and D multi-threaded versions, and tested their results to Ruby. First, study my code to know exactly what and why its doing. Then start slow. Know what and why the results should be at each stage of your code for each section. The algorithm is very simple, if you understand it. Once you do, you can run it on any platform in your language(s) of choice. If you need help post code on git[hub\|lab], or a gist, or email me.

2020-10-24, 14:20	#58
jzakiya Jul 2014 2⁵ Posts	There's a Rust forum post (2020/10/22) about a package to use Rust on GPUs. https://users.rust-lang.org/t/introd...-gpu-0-1/50499 I don't have a GPU, so I don't have the hardware to play with it. For those who do, this package should (?) provide the basics to implement the algorithm on GPUs, which (if properly done) increase performance significantly, while extending the number space range too. https://github.com/EmbarkStudios/rus...eases/tag/v0.1