Accelerating AI tasks while preserving data security
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
Electronics
New techniques efficiently accelerate sparse tensors for massive AI models
Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.
System combines light and electrons to unlock faster, greener computing
“Lightning” system connects photons to the electronic components of computers using a novel abstraction, creating the first photonic computing prototype to serve real-time machine-learning inference requests.
Machine-learning system based on light could yield more powerful, efficient large language models
MIT system demonstrates greater than 100-fold improvement in energy efficiency and a 25-fold improvement in compute density compared with current systems.