Google

Google technology and systems.

Neural Turing Machines

~ Adrian Colyer ~ 15 Comments
Neural Turing Machines - Graves et al. 2014 (Google DeepMind) A Neural Turing Machine is a Neural Network extended with a working memory, which as we'll see, gives it very impressive learning abilities. A Neural Turing Machine (NTM) architecture contains two basic components: a neural network controller and a memory bank. Like most neural networks, ... Continue Reading

Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google’s Datacenter Network

~ Adrian Colyer ~ 1 Comment
Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network - Singh et. al (Google) 2015 Let's end the week with something completely different: a look at ten years and five generations of networking within Google's datacenters. Bandwidth demands within the datacenter are doubling every 12-15 months, even faster than the ... Continue Reading

The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing

~ Adrian Colyer ~ 10 Comments
The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing - Akidau et al. (Google) - 2015 With thanks to William Vambenepe for suggesting this paper via twitter. Google Cloud Dataflow reached GA last week, and the team behind Cloud Dataflow have a paper accepted at VLDB'15 ... Continue Reading

Heracles: Improving Resource Efficiency at Scale

~ Adrian Colyer ~ Leave a comment
Heracles: Improving Resource Efficiency at Scale - Lo et al. 2015 Until recently, scaling from Moore’s law provided higher compute per dollar with every server generation, allowing datacenters to scale without raising the cost. However, with several imminent challenges in technology scaling, alternate approaches are needed. Those approaches involve increasing server utilization, which is still ... Continue Reading