Multiplying the content of two x-y matrices together for screen rendering and AI processing. Matrix multiplication provides a series of fast multiply and add operations in parallel, and it is built ...

TPUs, on the other hand, are specialized in the sense that they only focus on certain processes. You can’t run a computer on a TPU: these chips are meant for fast tensor/matrix math. They don’t aim to ...

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.

Nexus proposes higher-order attention, refining queries and keys through nested loops to capture complex relationships.

Researchers from the University of Southern California Information Sciences Institute and the University of Wisconsin-Madison ...

Artificial intelligence has grown so large and power hungry that even cutting edge data centers strain to keep up, yet a technique borrowed from quantum physics is starting to carve these systems down ...

Being book smart is not the same as being street smart. Just because someone has a pile of degrees doesn’t mean that they ...

In this project, I implemented a high-performance matrix multiplication kernel using Triton, optimized for execution on NVIDIA T4 GPUs. The kernel computes D = ReLU(A × B + C) by leveraging shared ...

When the FORTRAN programming language debuted in 1957, it transformed how scientists and engineers programmed computers. Complex calculations could suddenly be expressed in concise, math-like notation ...

Define the Standard Model gauge group to be S ( U ( 2) × U ( 3)), the subgroup of SU ( 5) consisting of block diagonal matrices with a 2 × 2 block and then a 3 × 3 block. (This is isomorphic to the ...