The late physicists John Wheeler and Albert Einstein would have been overjoyed to see the recent confirmations of their hypothesis: gravity waves and black holes are out there, real and we can now detect them. Currently as of March 2018 6 major events have been detected, some of which have been simultaneously confirmed by independent telescope observation. The NSF funded Laser Interferometer Gravitational-Wave Observatory (LIGO) is a system that uses a laser interferometers to measure the strong gravity waves that are emitted when multiple black holes and other dense star types merge together. These incredibly strong waves ripple across the universe and are detected by multiple 4km long LIGO systems. LIGO went online with usable detection capabilities in Sept of 2015 and miraculously within 2 weeks observed its first gravitational wave detection. The raw data for these detectors are publicly available and the LIGO team has released a Jupyter notebook that shows the signal processing involved and narrows the search to the detection intervals. In addition they offer to the public a set of Python libraries than can be used to search across any time interval. This presentation will give a brief intro of the LIGO search algorithms and show how to get started to search for black holes with your own Ultra96 board or any other system capable of running Jupyter notebooks. There will be brief mention of how the Ultra96 FPGA could be used to accelerate the search algorithm’s signal processing.
YVR18-307:Detecting Binary Black Hole Mergers through LIGO Gravity Wave Measurements with Ultra96
BKK19-111 - DRM HW Composer for Beagle X15 BoardTuesday, April 16, 2019
Describing the process of adaptation AOSP DRM HWC to be used on Beagle X15 Board (4.14 kernel).
This can be used as an example of launching the external/drm_hwc on a board: a simple "How to" with the minimun steps required to get the drm_hwc functional.
SAN19-413 - TEE based Trusted Keys in LinuxFriday, October 4, 2019
Protecting key confidentiality is essential for many kernel security use-cases such as disk encryption, file encryption and protecting the integrity of file metadata. Trusted and encrypted keys provides a mechanism to export keys to user-space for storage as an encrypted blob and for the user-space to later reload them onto Linux keyring without the user-space knowing the encryption key. The existing Trusted Keys implementation relied on a TPM device but what if you are working on a system without one?
This session will introduce a Trusted Keys implementation which relies on a much simpler trusted application running in a Trusted Execution Environment (TEE) for sealing and unsealing of Trusted Keys using a hardware unique key provided by the TEE.