Google workloads for consumer devices: mitigating data movement bottlenecks

Google workloads for consumer devices: mitigating data movement bottlenecks Boroumand et al., ASPLOS'18 What if your mobile device could be twice as fast on common tasks, greatly improving the user experience, while at the same time significantly extending your battery life? This is the feat that the authors of today’s paper pull-off, using a technique … Continue reading Google workloads for consumer devices: mitigating data movement bottlenecks

The QUIC transport protocol: design and Internet-scale deployment

The QUIC transport protocol: design and Internet-scale deployment Langley et al., SIGCOMM’17 QUIC is a transport protocol designed from the ground up by Google improve the performance of HTTPS traffic. The chances are you’ve already used it - QUIC is deployed in Chrome, in the YouTube mobile app, and in the Google Search app on … Continue reading The QUIC transport protocol: design and Internet-scale deployment

TFX: A TensorFlow-based production scale machine learning platform

TFX: A TensorFlow-based production scale machine learning platform Baylor et al., KDD'17 What world-class looks like in online product and service development has been undergoing quite the revolution over the last few years. The series of papers we've been looking at recently can help you to understand where the bar is (it will have moved … Continue reading TFX: A TensorFlow-based production scale machine learning platform

Google Vizier: A service for black-box optimization

Google Vizier: a service for black-box optimization Golovin et al., KDD'17 We finished up last week by looking at the role of an internal (or external) experimentation platform. In today's paper Google remind us that such experimentation is just one form of optimisation. Google Vizier is an internal Google service for optimising pretty much anything. … Continue reading Google Vizier: A service for black-box optimization

BBR: Congestion-based congestion control

BBR: Congestion-based congestion control Cardwell et al., ACM Queue Sep-Oct 2016 With thanks to Hossein Ghodse (@hossg) for recommending today's paper selection. This is the story of how members of Google's make-tcp-fast project developed and deployed a new congestion control algorithm for TCP called BBR (for Bandwidth Bottleneck and Round-trip propagation time), leading to 2-25x … Continue reading BBR: Congestion-based congestion control

Strategic attentive writer for learning macro-actions

Strategic attentive writer for learning macro-actions Vezhnevets et al. (Google DeepMind), NIPS 2016 Baldrick may have a cunning plan, but most Deep Q Networks (DQNs) just react to what's immediately in front of them and what has come before. That is, at any given time step they propose the best action to take there and … Continue reading Strategic attentive writer for learning macro-actions