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Here are some of my notes from the first day of IPDPS. Optimizations & analysis of BSP graph processing models on public clouds Mapreduce/Hadoop is not very suitable for graph processing (which requires iterating over and over on the same graph), and this led to the Pregel graph processing framework by Google. Pregel is based on the Bulk Synchronous Parallelism (BSP) model. Here is a summary of Pregel if you are not familiar with it. In short, Pregel uses a vertex-centric graph processing model, where the same code is executed on all vertices concurrently. Pregel uses message passing along edges and barrier synchronization at supersteps (i.e., rounds) to iterate over the graph. This paper looks at optimizations and analysis of BSP graph processing frameworks. This group had access to Microsoft Azure cloud computing framework, and they wanted to experiment with Pregel there, so they implemented Pregel (following the description in the Pregel paper) from scratch in .NET envir

Last week I was in Boston to attend International conference on Parallel and Distributed Processing Systems (IPDPS) , and I will post some of my notes from this conference here. Coincidentally, Distributed Computing in Sensor Systems (DCOSS) was also being held at Boston at the same dates with IPDPS, and I could only reserve my room at the DCOSS hotel instead of the IPDPS hotel. Since the DCOSS keynote on mobile sensing by Hari Balakrishnan sounded more interesting to me than the IPDPS first day keynote, I decided to sneak in to the DCOSS room and attend that keynote instead. Hari's talk had two parts. He spent most of his time on the first part, and had to rush through the second part. How can sensors improve networks? The crossover happened this year: smartphone & tablets accessing the Internet overtook PCs & laptops accessing the Internet. Smartphone adoption rate is 7 times the rate of growth of world population, and there are more people using smartphones than pe

This paper, which appeared in NSDI 2013 , describes the evolution of Facebook’s memcached-based architecture. Memcached is an open-source implementation of a distributed in-memory hash table over a cluster of computers, and it is used for providing low latency access to a shared storage pool at low cost. Memcached was first developed by Brad Fitzpatrick in 2003. Memcached at Facebook targets a workload dominated by reads (which are two orders of magnitude more frequent than writes). Facebook needs to support a very heavy read load, over 1 billion reads/second, and needs to insulate backend services from high read rates with very high fan-out . To this end, Facebook uses memcache as a "demand-filled look-aside cache". When a web server needs data, it first requests the value from memcache by providing a string key. If it is a cache hit, great, the read operation is served. If the item addressed by that key is not cached, the web server retrieves the data from the backend da

I have been using the pomodoro technique for a couple years  to improve my productivity. Pomodoro is a timer (of 20 minutes) during which you commit to do a task. After this task timer there is a short break, after which the next task timer starts again. The pomodoro technique is described here in detail . I like pomodoro as it helps me to concentrate and get things done.  It also helps me to get started on something I detest doing: Surely I can endure doing that thing for 20 minutes, right? This helps trick myself to break my inertia and usually I find that I can keep going for multiple pomodoros on that task. I use the Pomodoro Desktop app (by Ugo Landini) for Mac OS X, and configure it to use 20 minutes as the task timer and 10 minutes as the break timer. I modified it to disable my laptop wifi at the start of the task timer and enable it back at the end of the task timer. For this I added  do shell script "networksetup -setairportpower en0 off"  to the pomodoro start

I had mentioned about Fatih Bulut, one of my PhD students, when writing about his crowdsourced line wait-time forecasting project . Fatih has recently been working on an energy-efficient proximity alert service for Android, and published his preliminary work in  M. F. Bulut, M. Demirbas. Energy Efficient Proximity Alert on Android. IEEE Workshop on Pervasive Collaboration and Social Networking, 2013 . The abstract from that paper reads: The proximity alert service on Android is important as an enabler of ubiquitous location-based services, however, it is also limited in this role due to its excessive energy expenditure. In this paper, we present the design and implementation of an energy-efficient proximity alert service for Android. Our method utilizes the distance to the point of interest and the user’s transportation mode in order to dynamically determine the location-sensing interval and the location providers (GPS, GSM, or Wi-Fi) to be used . We implement our method as a mid