How Google’s TPUs are reshaping the economics of large-scale AI

TPUv7 offers a viable alternative to the GPU-centric AI stack has already arrived — one with real implications for the economics and architecture of frontier-scale training.
IEEE

Accelerating Look-Up Table based Matrix Multiplication on GPUs

Abstract: Multiplying matrices is among the most fundamental and compute-intensive operations in machine learning. Approximated Matrix Multiplication (AMM) based on table look-ups can significantly ...
The Information

How Google’s AI Chips Stack Up to Nvidia’s

Google’s efforts to sell or lease its artificial intelligence server chips so they can run in any company’s data center—and not just in Google Cloud—have generated headlines, stock moves and a ...
IEEE

Optimizing the Complexity of Time in the Process of Multiplying Matrices in the Hill Cipher Algorithm Using the Strassen Algorithm

Abstract: Hill Cipher is one of the symmetric key cryptographic algorithms that have several advantages in data encryption. To avoid key invertible matrices, key matrices are generated using Newton's ...