Introducing PWL Mini!!
Starting this month we'll be opening up two 5-7 minute talk slots before our main talk. The idea is to share with the group a short summary of a paper or an idea that you are super excited about. Anyone can volunteer minis, just email us!
• Mini #1: Sargun Dhillon (https://twitter.com/sargun) on VL2 (http://research.microsoft.com/pubs/80693/vl2-sigcomm09-final.pdf), a paper by Microsoft Research about computer networking. VL2 leverages several novel schemes in order to build full-bisection, highly-scalable, and decentralized datacenter networks in an economical fashion. These networks continue to support the layer 2 and flat addressing semantics. Many modern networks have been greatly influenced by this design.
Sargun Dhillon (@sargun (https://gist.github.com/sargun/twitter.com/sargun)) is highly interested in schemes for efficient, flexible computer networks to enable the next generation of applications. He currently works at MustWin (http://mustwin.com/). He comes from an operations background, and spends much of his time thinking about how we can make distributed systems, networking, and databases friendlier to run.
Alex Rasmussen (https://twitter.com/alexras) presents the "Flat Datacenter Storage (http://css.csail.mit.edu/6.824/2014/papers/fds.pdf)" paper by Edmund B. Nightingale, Jeremy Elson,Jinliang Fan, Owen Hofmann, Jon Howell, and Yutaka Suzue. http://css.csail.mit.edu/6.824/2014/papers/fds.pdf
Alex tells us: " Flat Datacenter Storage (FDS) is, as the intro describes, "a high-performance, fault-tolerant, large-scale, locality-oblivious blob store". It's also a great example of how carefully thought-out co-design of software and hardware for a target workload can yield really impressive performance results, even in the presence of heterogeneity and operating at scale. In my (admittedly biased) opinion, this style of system design doesn't get enough attention outside of academia, and has a lot to teach us about how data-intensive systems should be designed."
If you have any questions, thoughts, or related information, please visit our *github-thread* on the matter: https://github.com/papers-we-love/papers-we-love/issues/198
Alex Rasmussen (@alexras (https://twitter.com/alexras)) got his Ph.D. from UC San Diego in 2013. While at UCSD, he worked on really efficient large-scale data processing and set a few world sorting records, which makes him a hit at parties. He's currently working at Trifacta, helping build the industry's leading big data washing machine.
Doors open at 6:30 pm; the presentation will begin at 7:00 pm; and, yes, there will be beer and pizza.
After the paper is presented, we will open up the floor for discussion and questions.
We have selected a post meetup bar! After the meetup we'll head to Mars bar (http://www.marsbarsf.com/) (798 Brannan St) to have some drinks.