Using a grid, the system designs a set of rectangular silicon structures filled with tiny pores. The system continually adjusts each pixel in the grid until it arrives at the desired mathematical ...

Abstract: This paper presents ternary systolic array archi-tecture for matrix multiplication for ternary neural networks and image processing algorithms in ternary logic. As part of the architecture, ...

Abstract: Systolic array accelerators, a key implementation platform for modern neural networks, are vulnerable to malicious attacks such as directed bit flips and fault injections. These attacks ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

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 ...

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.

We audiophiles often say that our interest in gear is rooted in our love of music. That isn’t always truly the case, but in this instance, it is. My interest in the German pro-audio company Holoplot ...

Researchers claim to have developed a new way to run AI language models more efficiently by eliminating matrix multiplication from the process. This fundamentally redesigns neural network operations ...

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, ...