From f4d7cab3593e3bedce340c31886b0f74b013d16b Mon Sep 17 00:00:00 2001 From: Benoit Chevallier-Mames Date: Mon, 20 Sep 2021 11:41:03 +0200 Subject: [PATCH] doc: add a 'future feature' section closes #321 --- docs/user/explanation/FUTURE_FEATURES.md | 26 +++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/docs/user/explanation/FUTURE_FEATURES.md b/docs/user/explanation/FUTURE_FEATURES.md index a66f11b3f..8e608766e 100644 --- a/docs/user/explanation/FUTURE_FEATURES.md +++ b/docs/user/explanation/FUTURE_FEATURES.md @@ -1,3 +1,27 @@ # Future Features -Alex to do: #321 +As explained in [this section](FHE_AND_FRAMEWORK_LIMITS.md#concrete-framework-limits), the **Concrete Framework** +is currently in a preliminary version, and quite constrained in term of functionalities. However, the good +news is that we are going to release new versions regularly, where a lot of functionalities will be added progressively. + +In this page, we briefly list what the plans for next versions of the **Concrete Framework** are: +- **management of tensors**: today, we are mostly limited to scalars, but in the next version, the functions we compile +will possibly contain tensors, which is one of the basic features of `numpy` +- **better performance**: further versions will contain improved versions of the **Concrete Library**, with faster +execution; also, the **Concrete Compiler** will be improved, to have faster local execution (with multi-threading +for example) and faster production execution (with distribution over a set of machines or use of hardware accelerations) +- **more user-friendly API's**: we would like to make our API easier for a user. Notably, we would like to allow direct +compilations of classic Machine Learning framework models (e.g., tensorflow or pytorch) +- **more complete benchmarks**: we will have an extended benchmark, containing lots of functions that one day one would +want to compile; then, we will measure the framework progress by tracking the number of successfully compiled functions +over time. Also, this public benchmark will be a way for other competing frameworks or technologies to compare fairly +with us, in terms of functionality or performance +- **easier installation**: we plan to have pip installation of our framework very soon +- **Machine Learning helpers**: our midterm direction is to provide our users a set of tools to help her turn her use case +in an homomorphic equivalent. This set of tools will help her reduce the needed variable precision and/or optimize the +operations required to make the fastest possible compiled model. + +Also, if you are especially looking for some new feature, you can drop a message to . + + +