Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Engineers at MIT have turned one of computing’s biggest headaches, waste heat, into the main act. By sculpting “dust-sized” silicon structures that steer heat as precisely as electrical current, they ...

MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat ...

New silicon designs apply AI to processing and enhancing digital audio. Cadence has new IP to simplify the work.

Sparse matrix-matrix multiplication (SpMM) is a crucial kernel in various applications, including sparse deep neural networks [1]–[6], graph analytics [7], triangle counting [8], and linear algebra ...

Silicon photonics is the study of the optical properties of the group-IV semiconductor and the design and fabrication of devices for generating, manipulating and detecting light. Silicon is prevalent ...

Abstract: While sparsity, a feature of data in many applications, provides optimization opportunities such as reducing unnecessary computations, data transfers, and storage, it causes several ...

This project is intended for research purposes only. Use it at your own risk and discretion. Triton is a language and compiler for writing highly efficient ML primitives, one of the most common ...