Name: High-Performance and Data-Intensive Computing (HPDIC) research lab
Type: User
Company: University of Washington
Bio: The HPDIC research lab at the University of Washington publishes research findings at top conferences (e.g., SIGMOD, AAAI) and journals (e.g. TPAMI, TPDS).
Location: Seattle
Blog: https://hpdic.github.io/
High-Performance and Data-Intensive Computing (HPDIC) research lab's Projects
A collection of encrypted search algorithms
Mirror of Apache AsterixDB
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
✨ Awesome - A curated list of amazing Homomorphic Encryption libraries, software and resources
A curated list of multi party computation resources and links.
Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning
Building Java Programs 5th Edition Code Examples
Lightweight emulation of blockchains
Build Your Own Programming Language, published by Packt
The BusTub Relational Database Management System (Educational)
Mirror of Apache Cassandra
Cross-Blockchain Transactions
Charm: A Framework for Rapidly Prototyping Cryptosystems
Homomorphic comparison in leveled homomorphic encryption and its applications
A database system that can process SQL queries over encrypted data.
cryptography is a package designed to expose cryptographic primitives and recipes to Python developers.
Source Code for 'Cryptography and Cryptanalysis in Java' by Stefania Loredana Nita and Marius Iulian Mihailescu
A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
CUDA-accelerated Fully Homomorphic Encryption Library
DANNY is a decentralized vector database for building vector search applications
New Blockchain protocols for edge computing
Python implementation of the elgamal crypto system
Hyperledger Fabric is an enterprise-grade permissioned distributed ledger framework for developing solutions and applications. Its modular and versatile design satisfies a broad range of industry use cases. It offers a unique approach to consensus that enables performance at scale while preserving privacy.
A library for efficient similarity search and clustering of dense vectors.
CVPR 2022: FedCorr: Multi-Stage Federated Learning for Label Noise Correction
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
The fully homomorhic encryption scheme based on NTRU and LWE.