Andromeda: performance, isolation, and velocity at scale in cloud network virtualization

Andromeda: performance, isolation, and velocity at scale in cloud network virtualization Dalton et al., NSDI'18 Yesterday we took a look at the Microsoft Azure networking stack, today it’s the turn of the Google Cloud Platform. (It’s a very handy coincidence to have two such experience and system design report papers appearing side by side so ... Continue Reading

SmoothOperator: reducing power fragmentation and improving power utilization in large-scale datacenters

SmoothOperator: reducing power fragmentation and improving power utilization in large-scale datacenters Hsu et al., ASPLOS'18 What do you do when your theory of constraints analysis reveals that power has become your major limiting factor? That is, you can’t add more servers to your existing datacenter(s) without blowing your power budget, and you don’t want to ... Continue Reading

WSMeter: A performance evaluation methodology for Google’s production warehouse-scale computers

WSMeter: A performance evaluation methodology for Google’s production warehouse-scale computers Lee et al., ASPLOS'18 (The link above is to the ACM Digital Library, if you don’t have membership you should still be able to access the paper pdf by following the link from The Morning Paper blog post directly.) How do you know how well ... Continue Reading

The architectural implications of autonomous driving: constraints and acceleration

The architectural implications of autonomous driving: constraints and acceleration Lin et al., ASPLOS'18 Today’s paper is another example of complementing CPUs with GPUs, FPGAs, and ASICs in order to build a system with the desired performance. In this instance, the challenge is to build an autonomous self-driving car! Architecting autonomous driving systems is particularly challenging ... Continue Reading