A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...

AMD researchers argue that, while algorithms like the Ozaki scheme merit investigation, they're still not ready for prime time. Double precision floating point computation (aka FP64) is what keeps ...

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.

Understanding the benefits of matrix converters for EV chargers and a comparison of different matrix converter topologies.

Abstract: Exploiting the numeric symmetry in sparse matrices to reduce their memory footprint is very tempting for optimizing the memory-bound Sparse Matrix-Vector Multiplication (SpMV) kernel.

Given the rapidly evolving landscape of Artificial Intelligence, one of the biggest hurdles tech leaders often come across is ...

Abstract: We present a strictly balanced method for the parallel computation of sparse matrix-vector products (SpMV). Our algorithm operates directly upon the Compressed Sparse Row (CSR) sparse matrix ...

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 ...

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 ...

This implementation creates a sophisticated knowledge retrieval system by integrating KAG methodologies with traditional RAG approaches. It seamlessly combines Graphiti's graph intelligence, Qdrant's ...