MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...

Learn how to solve linear systems using the matrix approach in Python. This video explains how matrices represent systems of equations and demonstrates practical solutions using linear algebra ...

NVIDIA releases detailed cuTile Python tutorial for Blackwell GPUs, demonstrating matrix multiplication achieving over 90% of cuBLAS performance with simplified code. NVIDIA has published a ...

SiFive’s New RISC-V IP Combines Scalar, Vector and Matrix Compute to Accelerate AI from the Far Edge IoT to the Data Center New X100 Series Joins Upgraded X200, X300 and XM IP to Address Growing ...

SANTA CLARA, Calif.--(BUSINESS WIRE)--Further expanding SiFive’s lead in RISC-V AI IP, the company today launched its 2nd Generation Intelligence™ family, featuring five new RISC-V-based products ...

IBM's new Power11 servers aim to address growing modernization needs in the enterprise datacenter, expanding the Power lineup to cover new use cases. IBM recently achieved its highest market cap ever.

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 ...

Abstract: While the Karatsuba algorithm reduces the complexity of large integer multiplication, the extra additions required minimize its benefits for smaller integers of more commonly-used bitwidths.

This paper presents an open-source library that pushes the limits of performance portability for irregular General Matrix Multiplication (GEMM) on the widely-used Arm architectures. Our library, ...

Discover how nvmath-python leverages NVIDIA CUDA-X math libraries for high-performance matrix operations, optimizing deep learning tasks with epilog fusion, as detailed by Szymon Karpiński.