“Several manufacturers have already started to commercialize near-bank Processing-In-Memory (PIM) architectures. Near-bank PIM architectures place simple cores close to DRAM banks and can yield ...

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

MIT engineers use heat-conducting silicon microstructures to perform matrix multiplication with >99% accuracy hinting at ...

This third course in the specialization focuses on modeling requirements. It is highly recommended that students take the first two courses that focus on the core structure in any autonomous system ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...

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 ...

Researchers from the Institute for Artificial Intelligence at Peking University, led by Sun Zhong, have developed a high-precision and scalable analogue matrix computing chip based on RERAM, which ...