Taiji: managing global user traffic for large-scale Internet services at the edge

Taiji: managing global user traffic for large-scale internet services at the edge Xu et al., SOSP'19 It’s another networking paper to close out the week (and our coverage of SOSP’19), but whereas Snap looked at traffic routing within the datacenter, Taiji is concerned with routing traffic from the edge to a datacenter. It’s been in … Continue reading Taiji: managing global user traffic for large-scale Internet services at the edge

HackPPL: a universal probabilistic programming language

HackPPL: a universal probabilistic programming language Ai et al., MAPL'19 The Hack programming language, as the authors proudly tell us, is "a dominant web development language across large technology firms with over 100 million lines of production code." Nail that niche! Does your market get any smaller if we also require those firms to have … Continue reading HackPPL: a universal probabilistic programming language

Applied machine learning at Facebook: a datacenter infrastructure perspective

Applied machine learning at Facebook: a datacenter infrastructure perspective Hazelwood et al., _HPCA’18 _ This is a wonderful glimpse into what it’s like when machine learning comes to pervade nearly every part of a business, with implications top-to-bottom through the whole stack. It’s amazing to step back and think just how fundamentally software systems have … Continue reading Applied machine learning at Facebook: a datacenter infrastructure perspective

Maelstrom: mitigating datacenter-level disasters by draining interdependent traffic safely and efficiently

Maelstrom: mitigating datacenter-level disasters by draining interdependent traffic safely and efficiently Veeraraghavan et al., OSDI'18 Here’s a really valuable paper detailing four plus years of experience dealing with datacenter outages at Facebook. Maelstrom is the system Facebook use in production to mitigate and recover from datacenter-level disasters. The high level idea is simple: drain traffic … Continue reading Maelstrom: mitigating datacenter-level disasters by draining interdependent traffic safely and efficiently

Rosetta: large scale system for text detection and recognition in images

Rosetta: large scale system for text detection and recognition in images Borisyuk et al., KDD'18 Rosetta is Facebook’s production system for extracting text (OCR) from uploaded images. In the last several years, the volume of photos being uploaded to social media platforms has grown exponentially to the order of hundreds of millions every day, presenting … Continue reading Rosetta: large scale system for text detection and recognition in images

Unveiling and quantifying Facebook exploitation of sensitive personal data for advertising purposes

Unveiling and quantifying Facebook exploitation of sensitive personal data for advertising purposes Cabañas et al., USENIX Security 2018 Earlier this week we saw how the determined can still bypass most browser and tracker-blocking extension protections to track users around the web. Today’s paper is a great example of why you should care about that. Cabañas … Continue reading Unveiling and quantifying Facebook exploitation of sensitive personal data for advertising purposes

HHVM JIT: A profile-guided, region-based compiler for PHP and Hack

HHVM JIT: A profile-guided, region-based compiler for PHP and Hack Ottoni, PLDI'18 HHVM is a virtual machine for PHP and Hack (a PHP extension) which is used to power Facebook’s website among others. Today’s paper choice describes the second generation HHVM implementation, which delivered a 21.7% performance boost when running the Facebook website compared to … Continue reading HHVM JIT: A profile-guided, region-based compiler for PHP and Hack