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Sontungmtp
@sontungmtp.eth
Exploring Fully Homomorphic Encryption Today's digital world faces the challenge of keeping data safe while still being able to use it > FHE allows computations to be performed on encrypted data without ever needing to decrypt it, significantly enhancing data security > This article dive deep into FHE, from theory to real-world applications
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Gop
@guop
SIMD batching: Single Instruction, Multiple Data (SIMD) batching is a pivotal performance metric in FHE that impacts its efficiency and scalability. By enabling multiple data points to be encrypted into a single ciphertext, SIMD batching allows simultaneous operations on all these data points. This parallel processing capability is especially beneficial for vector operations common in machine learning and statistical analysis, significantly reducing the computational overhead and latency compared to processing data points individually.
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