Prasun Chaudhuri speaks to expert Subrata Das about the opportunities. Das is currently an adjunct faculty member at Northeastern University in Boston, US, where he teaches generative AI ...

A vector (1st order tensor) is an array of numbers in one dimension with a single indice A matrix (2nd order tensor) is table of numbers in two dimensions with two indices ...

Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within ...

Performance issue description Hello, I am exploring the landscape of CPU inference, specifically for latency sensitive applications, and benchmarking various implementations. To test this, I did the ...

Matrix multiplication (MatMul) is a fundamental operation in most neural networks, primarily because GPUs are highly optimized for these computations. Despite its critical role in deep learning, ...

The Matrix Revolutions Matrix multiplication advancement could lead to faster, more efficient AI models At the heart of AI, matrix math has just seen its biggest boost "in more than a decade.” ...

A Laser Focus In 1986, Strassen had another big breakthrough when he introduced what’s called the laser method for matrix multiplication. Strassen used it to establish an upper value for omega of 2.48 ...

Figure 2: Semidynamics’ Tensor Unit (Source: Semidynamics) Espasa said the Tensor Unit can be used for layers that require matrix multiplication, such as fully connected and convolutional layers, ...