This month, our team at Zama released a new version of TFHE-rs (v0.7), alongside new versions of Concrete (v2.7), Concrete ML (v1.6) and the fhEVM (v0.5). With these releases, Zama continues to build its suite of products to make homomorphic encryption accessible, easy, and fast.
TFHE-rs v0.7 now supports the compression of ciphertexts that encrypt the result of some homomorphic computations. This new feature reduces the size of ciphertexts by up to 1,900x with the provided parameters! Additionally, TFHE-rs v0.7 allows users to leverage multi-GPU architectures, which are widely deployed on servers, to drastically enhance computational performance.
Read the full release blog post here
Concrete v2.7 introduces the first wheel that can accelerate computations on GPUs! In this new release, we also extend the support for function composition, and add several new features in the Python frontend for the user.
Read the full release blog post here
Concrete ML v1.6 improves latency on large neural networks, adds support for pre-trained tree-based models and eases collaborative computation by introducing DataFrame schemas and by facilitating the deployment of logistic regression training. While GPU support will be available very soon in Concrete ML, some early latency results are given in the blog post.
Read the full release blog post here
fhEVM v0.5 introduces many significant enhancements to improve the security and efficiency of handling encrypted data in your applications, including packed input mechanism, enhanced Access Control List (ACL), and updated decryption and re-encryption process. Most importantly, starting from fhEVM v0.5, the Solidity API comes into a stable and finalized version that will be compatible for future versions and across various chains.
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