Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using ...

Varying the cache size the respective miss rates in the L1 cache are taken and then comparison is done. It is found that the miss rates in the L1 cache for the cache oblivious matrix multiplication ...

In matrix algebra, the inverse of some matrix A is a matrix Ainv if A * Ainv = Ainv * A = I, where * indicates matrix multiplication, and I is the identity matrix (1.0 values on the upper-left to ...

To multiply numbers from matrices on different GPUs, data must be moved around, a process which creates most of the neural network’s costs in terms of time and energy. Eliminating matrix ...

Modular Mojo is a new programming language designed for AI developers that is said to combine the usability of Python with the performance of C with over 36,000 times the performance of Python on a ...

We will learn some divide and conquer algorithms for Integer Multiplication (Karatsuba’s Algorithm), Matrix Multiplication (Strassen’s Algorithm), Fast Fourier Transforms (FFTs), and Finding Closest ...

Because of C++11, C++ was slowly going uphill in the TIOBE index after having been in a constant decline since 2001. The second land mark is the recent C++20 publication," notes Jensen.

The second subfield thinks on a smaller scale. Soon after Strassen’s work, the Israeli American computer scientist Shmuel Winograd showed that Strassen had reached a theoretical limit: It’s not ...

Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...

Tensor for matrix multiplication and algorithms: here multiplication of 2 x 2 matrices. Entries equal to 1 are purple, 0 entries are semi-transparent.