DIMPACT

Sustainability is now a key focus for the digital advertising industry. Last year, it was estimated that a typical ad campaign emitted around 5.4 tons of CO2, with a programmatic ad impression producing around one gram of Co2 emissions. When the number of ad impressions transacted on a regular basis…

We're excited to announce a proposed standard for assessing technology-related carbon emissions – an approach to classifying an organisation's technology footprint in a way that enables consistent analysis and benchmarking of the carbon impact, aligned with the GHG protocol.

Towards environmentally sustainable computational science

Dead Simple Sites curates the most minimal sites on the web.

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L'intelligence collective est un levier pour déployer la démarche d'écoconception numérique dans une organisation : on vous explique pourquoi

L’écoconception numérique continue à se développer en France, notamment portée par le nouveau réglement général d’écoconception de services numériques (RGESN) développé au sein de l’État. Cette pratique consiste à se demander quoi faire pour réduire la charge environnementale (émissions de gaz à effet de serre, consommation d’énergie, d’eau, etc.) d’un site web et de son usage. Nous avons maintenant une certaine expérience du sujet puisque nous explorons à la fois en théorie et en pratique depuis 5 ans toutes ces questions. La refonte de Telecoop s’inscrit d’ailleurs dans la continuité de celle pour Commown avec Derek Salmon. Dans cette étude de cas, nous allons tâcher d’appliquer ce fameux RGESN qui se distingue par 8 grands axes : la stratégie, les spécifications, l’architecture, l’UX/UI, les contenus, le front-end, le back-end, l’hébergement. Nous allons reprendre point par point chacun de ces éléments.

Découvrez la conférence de Christophe Clouzeau, qui présente l'importance d'une écoconception et de l'impact environnemental du numérique.

Achieving the UN Sustainable Development Goals (SDGs) demands a shift by industry, governments, society, and individuals to reach adequate levels of a…

Smart coders can see the system is broken

Learn about optimizing your Azure carbon emissions.

Deep Learning (DL) frameworks such as PyTorch and TensorFlow include runtime infrastructures responsible for executing trained models on target hardware, managing memory, data transfers, and multi-accelerator execution, if applicable. Additionally, it is a common practice to deploy pre-trained models on environments distinct from their native development settings. This led to the introduction of interchange formats such as ONNX, which includes its runtime infrastructure, and ONNX Runtime, which work as standard formats that can be used across diverse DL frameworks and languages. Even though these runtime infrastructures have a great impact on inference performance, no previous paper has investigated their energy efficiency. In this study, we monitor the energy consumption and inference time in the runtime infrastructures of three well-known DL frameworks as well as ONNX, using three various DL models. To have nuance in our investigation, we also examine the impact of using different execution providers. We find out that the performance and energy efficiency of DL are difficult to predict. One framework, MXNet, outperforms both PyTorch and TensorFlow for the computer vision models using batch size 1, due to efficient GPU usage and thus low CPU usage. However, batch size 64 makes PyTorch and MXNet practically indistinguishable, while TensorFlow is outperformed consistently. For BERT, PyTorch exhibits the best performance. Converting the models to ONNX usually yields significant performance improvements but the ONNX converted ResNet model with batch size 64 consumes approximately 10% more energy and time than the original PyTorch model.

Alter Numeris, ce sont des chercheurs et des penseurs qui réfléchissent les enjeux de la société numérique.

If you want to save money in Enterprise IT, it turns out that sustainability as a KPI is more important than cost - this is one of the key findings coming from the recent GreenOps Survey, some research made possible by the recent ClimateAction MiniGrants fund.

Pistes d'interfaces pour un design écologique des paramètres sur mobile.

In this post, I want to look at the two different carbon accounting models used for estimation, and in what scenario you might use one over the other.

Als ervaren digitale experts helpen we organisaties met toegankelijke technologie. Strategie, UX, websites, technologie, online marketing...

Récemment, on m’a posé la question de savoir si un site plein de visuels et de grandes images pouvait être considéré comme éco-conçu si on l’optimisait à mort. Alors : éco-conception web = frugalité des contenus ou optimisations techniques ?