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Modern (consolidated) RADIUS configuration

Materials for Stanford's EE185 course, Interactive Light Sculpture Project.

The "lbcd" shared module

The "base" shared module.

Manage the AFS client (either OpenAFS or AuriStor) on a Stanford machine.

Stanford Apache module.

Puppet agent installation bootstrap script.

Fine-Grained Memory Access Profiling for GCRAM-Based AI Accelerators. Profiler to provide insight into relevant metrics such as data lifetimes and read/write frequencies to guide DSE of gain cell-based on-chip memories in domain specific hardware.

MINT is a Python package that streamlines integration of multilayer networks for multimodal community detection (subtyping). MINT is comprised of several modules crafted to: standardize input data, execute Spectral Neighbor-joining Fusion (SNF) and Generalized Louvain (GenLouvain) algorithms, visualize intermediate results, perform cross-validation techniques, and optimize the identified communities by selecting an optimal combination of modalities that maximizes the silhouette score.

Contact: Dr. Saman Sarraf (ssarraf@stanford.edu), Dr. Hadi Hosseini (study_brain@stanford.edu)

Public website (https://gainsight.stanford.edu) for releasing documentation, Tableau-based visualizations, and artifacts related to the GainSight project.