From ed3b29ba7971bba611cc3112cf6c620734a309d3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Javier=20Gonz=C3=A1lez-Delgado?= <jgonzalezd@laas.fr>
Date: Fri, 26 Apr 2024 16:24:04 +0000
Subject: [PATCH] Update README.md

---
 README.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 7d2eb42..c710405 100644
--- a/README.md
+++ b/README.md
@@ -38,7 +38,7 @@ wario-notebooks
 ```
 opens the ready-to-use jupyter notebook.
 
-The installation procedure works correctly with recent versions of Linux (Ubuntu 20.04 and 22.04) and MacOS (Sonoma 14.4.1) operating systems. Typical install time on a normal desktop computer is around 5 minutes. If you encounter any trouble to install WARIO, please file an [issue](https://gitlab.laas.fr/moma/methods/analysis/WARIO/-/issues) or [contact us](mailto:javier.gonzalez-delgado@math.univ-toulouse.fr).
+The installation procedure works correctly with recent versions of Linux (Ubuntu 20.04 and 22.04) and MacOS (Sonoma 14.4.1) operating systems. Typical install time on a normal desktop computer is around 5 minutes. If you encounter any trouble to install WARIO, please file an [issue](https://gitlab.laas.fr/moma/methods/analysis/WARIO/-/issues) or [contact us](mailto:javier.gonzalezdelgado@mcgill.ca).
 
 ## DEMO (data example)
 
@@ -75,3 +75,6 @@ By setting the clustering precision at the default level (i.e. minimum cluster s
 
 Each cluster can be complementary described by the average DSSP propensities of its conformations. The corresponding plots are available [here](https://gitlab.laas.fr/moma/methods/analysis/WARIO/-/tree/main/wario/demo).
 
+## Large ensembles
+
+The current implementation of WARIO can be run in a normal desktop computer for ensembles with $nL\lessapprox 3\cdot 10^7$. Limitations are mainly due to memory constraints. We are currently working on a more efficient implementation for large ensembles, that can be run in remote servers for larger ensembles. Until it is released, we can [provide guidance](mailto:javier.gonzalezdelgado@mcgill.ca) on how to more efficiently run the current code in limiting settings $nL\approx 3-4\cdot 10^7$.
-- 
GitLab