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
LVC20-205 Running ACS on Arm's Neoverse Reference Design PlatformsMonday, September 21, 2020
The Arm ServerReady compliance program provides a solution to ensure that the Arm servers comply to standards at both hardware and firmware interface. The Arm’s Server Architectural Compliance Suite (ACS) is such a solution and covers the compliance validation for hardware requirements (SBSA) and firmware requirements (SBBR).
This presentation talks about running ACS on Arm servers with specific focus on experiences of running ACS on Arm’s Neoverse Reference Design (RD) platforms. Key takeaways for audience include short introduction of SBSA and SBBR test cases, procedures of running ACS, important aspects at the platform software level for SBSA and SBBR compliance and ACS test results for Arm’s Neoverse RD platforms. This session acts as a quick start guide for running ACS on an Arm platform and uses Arm’s Neoverse Reference Design (RD) platform as an example.
SAN19-306 - The Convergence of Big Data and AIFriday, October 4, 2019
Big Data is one of the key use cases for Arm servers, and the Big Data frameworks like Hadoop and Spark have been enabled generally for Arm architecture, while the capabilities of Artificial Intelligence and Machine Learning in the Big Data frameworks can be important for vendors to have competitive solutions with Arm servers. This session will do some introduction about the ecosystem to integrate AI with Big Data, and some collaboration opportunities in the community can be discussed.
LVC21-310: Unifying Kernel Test Reporting with KernelCIThursday, March 25, 2021
The landscape of Linux kernel testing and CI is notoriously fragmented. Systems like Linaro's LKFT, Intel's 0day, Google's Syzbot, Red Hat's CKI, and others, are each running their own tests, sending separate emails, and hosting different dashboards. As a result, developers have to cope with multiple diverse reports arriving at various stages of development cycle, and it's difficult to correlate and analyze results. The Linux Foundation's KernelCI project has been working on a CI stack and service for all to use, which is seeing increasing adoption. However, the project has also started a new effort aimed at already-established CI systems, letting participants keep their setups, but submit testing results to a common database and reporting system, using a simple, extensible protocol. The system behind the new effort is called "KCIDB" (for "KernelCI Database") and is already receiving reports from the native KernelCI tests, RedHat's CKI and Google's Syzbot, with more systems working on joining. Our aim is to develop a unified report protocol and schema, maintain an open result database, provide a single dashboard, and to send email notifications aggregating the data from all the participating systems. We want to reduce developer load, and make it easier to discover and analyze kernel testing results. Join this session to find out how far we've got, how our dashboard and email notifications look, how we're pulling this off, what the protocol and the schema is like, and how to start sending your reports or join the development.
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