Sergei Vorobyov

Memory constraints in neural network verification can be drastically reduced by leveraging parallelism techniques, enabling more extensive and efficient safety property checks.

Training Llama3-8B with 5M context on a single node is now possible, thanks to a simple head-wise chunking strategy that slashes memory use by 87.5%.