Online reconstruction of structural information from datacenter logs

Online reconstruction of structural information from datacenter logs Chothia et al., EuroSys'17 Today's choice brings together a couple of themes that we've previously looked at on The Morning Paper: recovering system information from log files, and dataflows for stream processing. On log files (and tracing), see for example Dapper, the MysteryMachine, lprof, and Pivot tracing. … Continue reading Online reconstruction of structural information from datacenter logs

Mosaic: processing a trillion-edge graph on a single machine

Mosaic: Processing a trillion-edge graph on a single machine Maass et al., EuroSys'17 Unless your graph is bigger than Facebook's, you can process it on a single machine. With the inception of the internet, large-scale graphs comprising web graphs or social networks have become common. For example, Facebook recently reported their largest social graph comprises … Continue reading Mosaic: processing a trillion-edge graph on a single machine

An empirical study on the correctness of formally verified distributed systems

An empirical study on the correctness of formally verified distributed systems Fonseca et al., EuroSys'17 "Is your distributed system bug free?" "I formally verified it!" "Yes, but is your distributed system bug free?" There's a really important discussion running through this paper - what does it take to write bug-free systems software? I have a … Continue reading An empirical study on the correctness of formally verified distributed systems

Apps with hardware: enabling run-time architectural customization in smart phones

Apps with hardware: enabling run-time architectural customization in smart phones Coughlin et al., USENIX ATC'16 This week we've had a couple of hardware-related papers, and one touching on mobile apps (in the context of DNNs). Today's choice brings those themes together with some really creative thinking - programmable hardware for smartphones! With thanks to Afshaan … Continue reading Apps with hardware: enabling run-time architectural customization in smart phones

Neurosurgeon: collaborative intelligence between the cloud and the mobile edge

Neurosurgeon: collaborative intelligence between the cloud and mobile edge Kang et al., ASPLOS'17 For a whole class of new intelligent personal assistant applications that process images, videos, speech, and text using deep neural networks, the common wisdom is that you really need to run the processing in the cloud to take advantage of powerful clusters … Continue reading Neurosurgeon: collaborative intelligence between the cloud and the mobile edge

Determining application-specific peak power and energy requirements for ultra-low power processors

Determining application-specific peak power and energy requirements for ultra-low power processors Cherupalli et al., ASPLOS'17 We're straying a little bit out of The Morning Paper comfort zone again this morning to look at one of the key hardware issues affecting the design of IoT devices: how much energy they use, and the related question of … Continue reading Determining application-specific peak power and energy requirements for ultra-low power processors