Month: November 2017

Concrete problems in AI safety

~ Adrian Colyer ~ 7 Comments
Concrete problems in AI safety Amodei, Olah, et al., arXiv 2016 This paper examines the potential for accidents in machine learning based systems, and the possible prevention mechanisms we can put in place to protect against them. We define accidents as unintended and harmful behavior that may emerge from machine learning systems when we specify ... Continue Reading

KV-Direct: High-performance in-memory key-value store with programmable NIC

~ Adrian Colyer ~ 14 Comments
KV-Direct: High-performance in-memory key-value store with programmable NIC Li et al., SOSP’17 We’ve seen some pretty impressive in-memory datastores in past editions of The Morning Paper, including FaRM, RAMCloud, and DrTM. But nothing that compares with KV-Direct: With 10 programmable NIC cards in a commodity server, we achieve 1.22 billion KV operations per second, which ... Continue Reading

Canopy: an end-to-end performance tracing and analysis system

~ Adrian Colyer ~ 1 Comment
Canopy: an end-to-end performance tracing and analysis system Kaldor et al., SOSP’17 In 2014, Facebook published their work on ‘The Mystery Machine,’ describing an approach to end-to-end performance tracing and analysis when you can’t assume a perfectly instrumented homogeneous environment. Three years on, and a new system, Canopy, has risen to take its place. Whereas ... Continue Reading