Engheta and colleagues have now set their sights on vector–matrix multiplication, which is a vital operation for the artificial neural networks used in some artificial intelligence systems. The team ...

Real PIM systems can provide high levels of parallelism, large aggregate memory bandwidth and low memory access latency, thereby being a good fit to accelerate the widely-used, memory-bound Sparse ...

However, the traditional incoherent matrix-vector multiplication method focuses on real-valued operations and does not work well in complex-valued neural networks and discrete Fourier transforms.

A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...

Sparse Matrix Multiplication October 1, 2015 by MichaelS Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the ...