About
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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The talk
Credits and licence
- Institution
- CERN
- Speaker
- Sebastien Viret
- Year
- 2026
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed