Parallelism Relevance
The other day I got rather caught up in the whole * is Unix discussion and wanted to get a better understanding of some of the more low level details associated with writing servers. Eventually, I had a crude version of CherryPy that forked instead of used threads. The benchmark in CherryPy seemed to suggest it was a great deal faster, but honestly I think that was a fluke, especially considering I'm pretty sure there are some serious deficiencies in terms of process management. When Bob posted his forking example on the CherryPy list and mentioned signals, it was clear that I was missing some pretty important understanding.
One thing I thought seemed helpful was that it seemed to use both processors on my system. My understanding is that calling fork will create two separate processes, which effectively should place at least some of the forked processes on different processors. My understanding is that this is how the multiprocessing module works (on Linux at least). With this new cursory knowledge under my belt it was interesting to see an article in my ACM Communications magazine remark on the future of computing and the need to handle multiple processors in a similar manner as sequential paradigms. I should note that this is one of the very few times there was anything remotely interesting to me in my ACM magazine, so I felt compelled to check it out. The idea is not new to me and while the arguments that this is a huge issue is pretty valid, I also started thinking that maybe it is not as big a deal in practice. The reason for this is the web. Back in the early days of computing people had dumb terminals and logged into a server where all the actual "computing" was performed. While thick clients have been the rage for quite a while, the web is effectively becoming the mainframe in the sky in terms of where people are doing their computing. This should be very helpful in making the jump to parallel computing because there s a definite history and set of tools that have been developed to scale that allow parallel processors. In other words, who really cares if your computer has 2 quad core processors when your searching email online, browsing facebook, checking your bank statements and reading the news through your web browser.On the web, what really matters is that the sites doing the processing have optimized their architectures to handle the load. The other side of the equation is the browser, but in reality, this is an area that is already becoming more robust. Google Chrome is a good example with its separate processes for each tab, but I would even argue that Javascript is well suited to handle distributed tasks. We've seen a ton of articles on using async servers. Javascript is already using an async model that is only getting faster with the recent developments in new Javascript engines. None of this means that parallel computing and utilization of more processors is not very important. I just don't think it is quite as critical as some might think. That doesn't mean programmers shouldn't try to understand it. After all, it is a hard problems and programmers typically like hard problems. My whole point though, is that the problem might be more of a fad than an actual crux for the IT industry.