Programming Non-Volatile Memory
School of Computer and Communication Sciences (IC) at EPFL (École Polytechnique Fédérale de Lausanne)”” –
New memory technologies are changing the computer systems landscape. Motivated by the power limitations of DRAM, new, non-volatile memory (NVM) technologies — such as ReRAM, PCM, and STT-RAM — are likely to be widely deployed in server and commodity computers in the near future. These memories erase the classical dichotomy between slow, non-volatile disks or SSDs and fast, volatile memory, greatly expanding the possible uses of durability mechanisms.
Taking advantage of non-volatility is not as simple as just writing data to NVM. Without programming support, it is challenging to write correct, efficient code that permits recovery after a power failure since the restart mechanism must find a consistent state in the durable storage. This problem is well-known in the database community, and a significant portion of a DB system is devoted to ensuring recoverability after failures.
James Larus is Professor and Dean of the School of Computer and Communication Sciences (IC) at EPFL (École Polytechnique Fédérale de Lausanne). Prior to joining IC in October 2013, Larus was a researcher, manager, and director in Microsoft Research for over 16 years and an assistant and associate professor in the Computer Sciences Department at the University of Wisconsin, Madison.
Rodrigo Seromenho Miragaia Rodrigues
IST Alameda – Anfiteatro Abreu Faro
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series takes place until July 16, between 17:30 and 18:30, via Zoom.
The seminars aims to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goals of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
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LxMLS 2020 – 10th Lisbon Machine Learning School
The 10th edition of Lisbon Machine Learning School, LxMLS, will take place from July 21st to July 29th at Instituto Superior Técnico (IST).
This event is organized by IST, Instituto de Telecomunicações (IT), INESC-ID, Unbabel, and Priberam Labs.
Applications until March 15th. For more information and to apply, access here.