Loose cables at CERN and Time synchronization is hard

According to sources familiar with the experiment, the 60 nanoseconds discrepancy appears to come from a bad connection between a fiber optic cable that connects to the GPS receiver used to correct the timing of the neutrinos’ flight and an electronic card in a computer. After tightening the connection and then measuring the time it takes data to travel the length of the fiber, researchers found that the data arrive 60 nanoseconds earlier than assumed. Since this time is subtracted from the overall time of flight, it appears to explain the early arrival of the neutrinos. New data, however, will be needed to confirm this hypothesis [ Science Insider]

Time synchronization is a real-time problem, meaning that every link is a single point of failure unless you engineer a lot of cross checking.  In our FSMLabs TimeKeeper software, we work in an environment that is a lot more complex and heterogeneous  than the CERN environment – fortunately we don’t need to get to those levels of precision. But we are operating at the under 1 microsecond level in many systems and it is enormously difficult to keep a running system balanced as network links misbehave, fans turn on and off,  and processor load changes. One thing we are increasingly doing is to monitor multiple time sources and track their relationships – to improve system resilience.


Manufacturing and devices

The answer is obvious but few people stop for a second to wonder about this. After all, it is not like Apple has control over all aluminum in the world. Apple were just the first to see the potential of such bodies and began to increase their orders. In just a few years Apple became the main partner of Catcher Technology, a company that possess the necessary expertise to manufacture such bodies. Apple’s production orders amount to 60% of the company’s production capacity. It takes three hours to create just a single body of this quality and, naturally, it is more expensive than a plastic body.[..]Thanks to the production scale these aluminum chassis cost Apple just as much as carbon fiber chassis cost to Sony and just a bit more expensive than plastic chassis for laptops of that price range.[…]

By now you must be wondering: why are they taking it? And if there is a short supply of aluminum bodies all they have to do is buy more CNC machinery and make all the chassis they need. But it’s not as simple as that: it takes up to a year to purchase, install and launch CNC equipment. The management also needs time and courage to allocate large funds to such a project. That is why it was so long before Apple got real competition in terms of laptop chassis. Asus purchased the necessary equipment some time ago but it began to work at full capacity just now and Asus UX21 is one of the first representatives of this work. And due to lower production volumes the production costs of these chassis are higher for Asus that for Apple. Besides, Apple is not paying for the equipment thanks to big binding contracts with their partners. [ Mobile-Review]

Julia programming language and hadoop

While we’re being demanding, we want something that provides the distributed power of Hadoop — without the kilobytes of boilerplate Java and XML; without being forced to sift through gigabytes of log files on hundreds of machines to find our bugs. We want the power without the layers of impenetrable complexity. We want to write simple scalar loops that compile down to tight machine code using just the registers on a single CPU. We want to write A*B and launch a thousand computations on a thousand machines, calculating a vast matrix product together. Julia

Aside from whatever merit the language has, the note about “kilobytes of boilerplate Java and XML” seems both wildly optimistic and on point.