4 papers
Privacy-Preserving AI Verification via Minimal Information Disclosure
Sleem Abdelghafar, Gabriel Kulp
AI verification crosses a trust boundary: a verifier must learn enough to establish an authorized claim, yet the same evidence can reveal sensitive details about the model, workloa…
Auditing Information Disclosure During LLM-Scale Gradient Descent Using Gradient Uniqueness
Sleem Abdelghafar, Maryam Aliakbarpour, Chris Jermaine
Disclosing information via the publication of a machine learning model poses significant privacy risks. However, auditing this disclosure across every datapoint during the training…
EinDecomp: Decomposition of Declaratively-Specified Machine Learning and Numerical Computations for Parallel Execution
Daniel Bourgeois, Zhimin Ding, Dimitrije Jankov +6
We consider the problem of automatically decomposing operations over tensors or arrays so that they can be executed in parallel on multiple devices. We address two, closely-linked…
TURNIP: A "Nondeterministic" GPU Runtime with CPU RAM Offload
Zhimin Ding, Jiawen Yao, Brianna Barrow +7
An obvious way to alleviate memory difficulties in GPU-based AI computing is via CPU offload, where data are moved between GPU and CPU RAM, so inexpensive CPU RAM is used to increa…