Prof. Williams now studies what happens when speed runs out.
Her field, fine-grained complexity, shows how close we are to the limits of computation and why some problems resist every shortcut.
#SimonsLive

Avoiding unnecessary data movement saves energy too! Holtz showed how communication-avoiding algorithms can find a sweet spot where less motion —> lower energy use and without slowing computation.
@SimonsInstitute #SimonsLive

‪Most of a computer’s effort isn’t doing math, it’s moving data, aka every trip between memory & processor = costs in time & power ‬
‪This is the communication cost, a framework researchers use to measure and reduce that hidden expense.‬
‪from Olga Holtz @SimonsInstitute #SimonsLive‬

How to make matrix multiplication practical

Mathematically:

- shrink the exponents and constants that set its speed

Hardware:

- move data less
- handle smaller chunks more efficiently

(from Oded Schwartz) @SimonsInstitute #SimonsLive

If we can multiply matrices even a little faster, the effects ripple outward. AI models could train more quickly, supercomputers could run with less energy, and data centers might draw less power from the grid. Efficiency here is environmental as much as intellectual. #SimonsLive

Matrix multiplication is the engine of modern computation. It powers neural networks, graphics, and massive data analysis. Every improvement changes what computers can do within the same energy and hardware limits. #SimonsLive

I’ll be here for the next month, following how researchers rethink one of the most fundamental operations in computing and how a small tweak in efficiency could reshape technology. #SimonsLive