zama-ai/tfhe-rs
Feb 2025 – Feb 2025
1 Month active
Languages Used
Rust
Technical Skills
AlgorithmsCryptographyData StructuresHomomorphic EncryptionLow-level Systems ProgrammingLow-level programming
Carl-Zama
PROFILE
Carl-zama
Carl Bootland contributed to the zama-ai/tfhe-rs repository by developing two core features that advanced tensor operations and cross-key homomorphic encryption workflows. He implemented efficient tensor slice decomposition iterators, enabling improved performance in tensor math and decomposition processes. Additionally, Carl added GLWE keyswitch functionality with supporting key generation, allowing GLWE ciphertexts to be transformed across different secret keys and facilitating more flexible homomorphic encryption workflows. His work leveraged Rust programming, low-level systems programming, and cryptography, demonstrating depth in both algorithmic design and practical implementation. Over the month, Carl focused on feature development, with no major bug fixes reported during this period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
1,966
Activity Months1
Your Network
69 people
Work History
February 2025
2 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for zama-ai/tfhe-rs: Delivered two core features advancing tensor operations and cross-key homomorphic encryption workflows; implemented efficient tensor slice decomposition iterators; added GLWE keyswitch functionality with key generation; no major bugs fixed this month; overall impact: improved performance and enable cross-key HE workflows; technologies: Rust, TFHE, GLWE, keyswitch, tensor decomposition iterators.
2 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for zama-ai/tfhe-rs: Delivered two core features advancing tensor operations and cross-key homomorphic encryption workflows; implemented efficient tensor slice decomposition iterators; added GLWE keyswitch functionality with key generation; no major bugs fixed this month; overall impact: improved performance and enable cross-key HE workflows; technologies: Rust, TFHE, GLWE, keyswitch, tensor decomposition iterators.
February 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance90.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Rust
Technical Skills
AlgorithmsCryptographyData StructuresHomomorphic EncryptionLow-level Systems ProgrammingLow-level programmingRust Programming
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