* Program re-ordering for improved L2 cache hit rate. * Automatic performance tuning. # Motivations # Matrix multiplications are a key building block of most modern high-performance computing systems.

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 ...

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.

The newly unveiled Mojo language is being promoted as the best of multiple worlds: the ease of use and clear syntax of Python, with the speed and memory safety of Rust. Those are bold claims, and ...

Matrix classes for matrices that are block-tridiagonal and sparse, and simply "block sparse". These talk together, and furthermore containts an algorithm for inversion of the block-tridiagonal version ...

Matrix-vector multiplications form the core of a plethora of scientific computing and machine learning applications that include solving partial differential equations, forward and back propagation in ...

Abstract: In distributed computing system for the master-worker framework, an erasure code is able to mitigate the effects of slow workers, also called stragglers. The distributed computing system ...