Students can plan their studies for board exam preparation with the official CBSE Class 12 Applied Maths syllabus (2026-27).

AI infrastructure startup Tensordyne has taped out its first commercial accelerator, with fabrication on TSMC's 3nm process ...

Transformations are the key to such codes, and they rely on math that predates computing as we know it by centuries. There ...

Triton is a language and compiler for writing highly efficient ML primitives, one of the most common primitive is matrix-multiplication. Triton typically builds these primitives using just-in-time ...

Combinatorial optimization (CO) underpins critical applications in science and engineering, ranging from logistics to electronic design automation. A classic example of CO is the NP-complete Traveling ...

CUDA-L2 is a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimize Half-precision General Matrix Multiply (HGEMM) CUDA kernels. CUDA-L2 ...

Matrix multiplication runs the modern world. For every word that ChatGPT writes, I estimate that ~10,000,000,000 (10 billion) small matrices must be multiplied. Modern gaming engines routinely draw 10 ...

Abstract: By combining the echoes of two channels in azimuth, and utilizing the super-resolution algorithm for ill-posed problems, the left/right ambiguity in forward-looking synthetic aperture radar ...

It’s a bright day for computing — literally. Two tech companies have unveiled computer components that use laser light to process information. These futuristic processors could soon solve specific ...

Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually ...

Abstract: Matrix operations are widely used in practical engineering, but the traditional processing methods rely on the loop iterations and neural network algorithm on the software, requiring a long ...