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 ...

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 ...

MicroCloud Hologram Inc. , ("HOLO" or the "Company"), a technology service provider, proposed an innovative hardware acceleration technology that converts the quantum tensor network algorithm into ...

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 ...

Scientists in the US have created a tiny silicon chip that can perform mathematical ...

“We must strive for better,” said IBM Research chief scientist Ruchir Puri at a conference on AI acceleration organised by the computer company and the IEEE in November. He expects almost all language ...

Numerical computation and mathematical software form the backbone of modern scientific inquiry, facilitating the approximation of real numbers, the solution of complex mathematical models, and the ...

Abstract: For many scientific applications, dense matrix multiplication is one of the most important and computation intensive linear algebra operations. An efficient matrix multiplication on high ...

Abstract: Sparse General Matrix-Matrix Multiplication (SpGEMM) is a core operation in high-performance computing applications such as algebraic multigrid solvers, machine learning, and graph ...