Abstract: Matrix multiplication is a fundamental computational operation widely used in various engineering applications. To accelerate large-scale matrix multiplication, computing tasks are commonly ...

Python turns 32. Explore 32 practical Python one-liners that show why readability, simplicity, and power still define the ...

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...

Multiplication in Python may seem simple at first—just use the * operator—but it actually covers far more than just numbers. You can use * to multiply integers and floats, repeat strings and lists, or ...

Discovering faster algorithms for matrix multiplication remains a key pursuit in computer science and numerical linear algebra. Since the pioneering contributions of Strassen and Winograd in the late ...

Google DeepMind today pulled the curtain back on AlphaEvolve, an artificial-intelligence agent that can invent brand-new computer algorithms — then put them straight to work inside the company's vast ...

Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.