From a228ae709b8d228a4128bec3f6c97939ea3efa01 Mon Sep 17 00:00:00 2001 From: Benoit Chevallier-Mames Date: Wed, 24 Jul 2024 10:57:43 +0200 Subject: [PATCH] Add Concrete compiler to 'Users of MLIR' --- website/content/users/_index.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/website/content/users/_index.md b/website/content/users/_index.md index 082b4ecc71b3..70b9c8bd2cb3 100644 --- a/website/content/users/_index.md +++ b/website/content/users/_index.md @@ -46,6 +46,22 @@ constantly evolving, aiming to deliver execution on heterogenous architectures w The CIRCT project is an (experimental!) effort looking to apply MLIR and the LLVM development methodology to the domain of hardware design tools. +## [Concrete](https://github.com/zama-ai/concrete): TFHE Compiler that converts python programs into FHE equivalent + +Concrete is an open-source framework that simplifies the use of +[Fully Homomorphic Encryption](https://fhe.org) (FHE) and makes writing FHE +programs easy for developers + +FHE is a powerful technology that enables computations on encrypted data without +needing to decrypt it. This capability ensures user privacy and provides robust +protection against data breaches. + +Concrete enables developers to efficiently develop privacy-preserving +applications for various use cases. For instance, +[Concrete ML](https://github.com/zama-ai/concrete-ml) is built on top of +Concrete to integrate privacy-preserving features of FHE into machine learning +use cases. + ## [Enzyme](https://enzyme.mit.edu): General Automatic Differentiation of MLIR Enzyme (specifically EnzymeMLIR) is a first-class automatic differentiation sytem for MLIR. Operations and types implement or inheret general interfaces