This is a bit old one, but an excellent article on how architectural complexity compares with body fat, on how architectural complexity needs to be kept at bay and what are some common patterns of increasing the complexity.
This was a read which came out of IETF’s article Reflections on Architecture which, among other things, highlights the differences between emergent complexity (which the author says is ok to have) and architectural complexity (which is not desirable and which is a result of poor design decisions – due to laziness or resource pressures).
To Install perf:
apt-get install linux-tools-common
apt-get install linux-tools-generic
apt-get install linux-tools-`uname -r`
To start monitoring a service using perf (for 10 seconds): (link from Brendan Gregg)
perf record -p PID sleep 10
To report usage
This article gives a very good introduction about what PCI “lanes” are, what is the difference between raw speed and data speed and how the old and new standards fare w.r.t speed.
This blog post does a nice job in summarizing the difference between three data centers based on various parameters. I have summarized the same as a table:
As I am going through Introduction to Algorithms course from MIT, just past the first lecture, we can see the importance of formally proving an algorithm correct. If an algorithm is intuitively incorrect at first, then the need for formal reasoning becomes even more important.
Coming to the 2-d peak finding algorithm, here is a semi-formal reasoning:
- When we find a global maximum in a column and shift to either left (right), it is because this global maximum is less than the left (right) element. So, if there is a new global maximum in this column, then it is definitely more than all the elements in the previous column because it is more than the left (element) itself. So, the algorithm works.
- Will the same argument apply if we find a 1-D peak in a column instead of a global maximum? Does not look to me like so…