I’m building a high-performance arithmetic system in Rust that rethinks number representation. By encoding integers as prime exponent vectors, it converts:
Multiplication → Vector addition
GCD/LCM → Min/Max operations
Matrix math → Optimized vector transforms
The core innovation exploits prime factorization’s mathematical properties. Modern hardware outperforms this approach for general cases of multiplication due to extreme optimization of traditional arithmetic. The key bottleneck is factorization latency (why RSA works). Today, it’s not viable for multiplication, but one can easily figure out the most efficient cases for it and combine the binary GCD algorithm with the PFS (Prime Factor System) algorithm and then we get an optimized version of the binary GCD and LCM algorithms (the second one is heavily based on GCD).
Future quantum integration could revolutionize multiplication too:
Shor’s algorithm would enable efficient factorization
Practical for huge numbers (n > 2^25 bits based on my calculations)
Turns prime vectors into an universal accelerator for many operations
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Once you ship this you can't edit the description of the project, but you'll be able to add more devlogs and re-ship it as you add new features!
Those are my final results, completed everything I wanted to do, my algorithm for gcd and lcm is slightly faster than binary gcd/lcm (the most used one atm), got nice graphs and everything but the benchmark for memory usage of the algorithms is working (but I am just unable to fix it atm and it's not that important for the project)
optimized algorithm, added a mix of standard calculations and pure cases, added stuff to gui, tried to add memory - it still has some issues tho
Wrote the whole algorithms in Rust, implemented binary gcd and lcm algorithms to compare, tried optimizing them a lot, could get my algorithm equal or faster until 12 bits of size. Also made a little GUI, to graph the results, the scale is from bottom to top in time (nanoseconds - ns) and from left to right in bits (4-32)
I changed some stuff, did some optimisations for the algorithms, implemented them in Rust, as python isn't that reliable for runtime tests, memory, etc. Tried to implement SIMD for the vector additions, implemented gcd and lcm for smaller than 32-bit numbers, ran some tests to check the performance - which was surprisingly good! cant push it to github rn tho, gonna do that tmrw, as im having some issues
I had a look at my previous work I did in python and tried to figure out, why the measurements were weird, it was because my factorization algorithm wasn't implemented correctly. The python version was just for basic testing, now as I'm doing it as an actual project I am going to switch to Rust, to have a better control over my memory, etc.
In the screenshot you can see a part of the code that I reviewed, it was on matrix multiplication with my method.