Dream - SED Sophia Antipolis Méditerrannée
Dream is the local name of CRISAM's service for supporting experiments & development, aka. SED.
Our service is composed of research engineers providing support for development, experiments and the management of experimental platforms. The team keeps up on technological advances.
This website is mainly used to provide blog posts about our activity. For institutional information, please visit the appropriate section on the Inria intranet.
To add a RSS feed to our blogposts, please click on the following link: https://iww.inria.fr/sed-sophia/feed.
To contact us, please send email to sed-sophia@inria.fr.
GPU benchmarks on Nef
During early summer 2020, we benchmarked recent GPU models available on Nef cluster for deep-learning using ResNet-50 model training, with ImageNet 2021 dataset and TensorFlow 2.0 official implementation. Please find here a summary of the results and lessons learnt. The different Nvidia GPU models tested are : GTX1080Ti a GeForce…
Estimating power consumption and carbon impact of deep-learning on Nef
Ecological impact of IT is an increasingly important matter. This is why estimating the impact of a computation is useful, both for assessing the cost of a research activity or designing efficient methods. Power consumption and carbon emissions of a computation are commonly used metrics, as this is a more…
Clean the jupyter notebooks in a git repository
# Context The jupyter notebooks contain both code to execute, outputs and metada related with the notebook. Among those metadata, there is by example the number of times (“execution_count”) a given cell has been run. Below is an extract of a notebook file, with in bold some of the data…
Summer 2020 Machine learning news
Here is a new series of interesting articles: PEGASUS: A State-of-the-Art Model for Abstractive Text Summarization from Google. Their hypothesis is that a pre-training task that’s closer to the final task will make the model better. To test this, their pre-training consist at trying to guess missing sentences (ex with…
