Hadoop Superlinear Scalability:
The perpetual motion of parallel performance
We often see more than 100 percent speedup efficiency! came the rejoinder to the innocent reminder that you can’t have more than 100 percent of anything. But this was just the first volley from software engineers during a presentation on how to quantify computer system scalability in terms of the speedup metric. In different venues, on subsequent occasions, that retort seemed to grow into a veritable chorus that not only was superlinear speedup commonly observed, but also the model used to quantify scalability for the past 20 years failed when applied to superlinear speedup data.
Dismantling the Barriers to Entry:
We have to choose to build a web that is accessible to everyone.
A war is being waged in the world of web development. On one side is a vanguard of toolmakers and tool users, who thrive on the destruction of bad old ideas ("old," in this milieu, meaning anything that debuted on Hacker News more than a month ago) and raucous debates about transpilers and suchlike. On the other side is an increasingly vocal contingent of developers who claim that the head-spinning rate of innovation makes it impossible to stay up to date, and that the web is disintegrating into a jumble of hacks upon opinions, most of which are wrong, and all of which will have changed by the time hot-new-thing.js reaches version 1.0.0.
Lazarus Code:
No one expects the Spanish Acquisition.
I’ve been asked to look into the possibility of taking a 15-year-old piece of open-source software and updating it to work on a current system used by my company. The code itself doesn’t seem to be too bad, at least no worse than the code I’m used to reading, but I suspect it might be easier to write a new version from scratch than to try to understand code that I didn’t write and which no one has actively maintained for several years. What is the point at which I should decide to ignore this old code and write something new?