# Tools for real-time inferences in GW detectors

- Institution: CERN
- Speaker: Sebastien Viret
- Year: 2026
- Language: English
- Source: [CERN](https://videos.cern.ch/record/3025629)
- Licence: [CERN](https://copyright.web.cern)
- Who can watch: Teens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Machine learning will play a key role in the next generation of interferometers data acquisition architectures, particularly through hardware-based solutions. However, methods deployed will have to meet very specific simplicity and robustness requirements. We will present those constraints and the tools we are currently developing to fulfill them at different hardware stages:

* **TolmNet**: a C program included in the Virgo online software framework to perform neural network inference in real-time computing environment. * **pyML2FPGA**: a python framework based on an HDL library converting a network into a ressources/latency optimized VDHL code which can be ported to a low-end FPGA.

In both cases, we present the results obtained so far using as an input a simple gravitational wave detection network.

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## Lectures

1. [Tools for real-time inferences in GW detectors](https://invisiblenetwork.ai/learn/cern/3025629/74f5d811d804), 27 min (CERN's player)