On Wed, 19 Sep 2007 19:14:39 -0700, Paul Rubin wrote: > We get cpu speed increases now through parallelism, not mhz. Intel and > AMD both have 4-core cpu's now and Intel has a 16-core chip coming. > Python is at a serious disadvantage compared with other languages if the > other languages keep up with developments and Python does not.
I think what you mean to say is that Python _will be_ at a serious disadvantage if other languages keep up and Python doesn't. Python can't be at a disadvantage _now_ because of what happens in the future. Although, with the rapid take-up of multi-core CPUs, the future is *really close*, so I welcome the earlier comment from Terry Reedy that Guido has said he is willing to make changes to the CPython internals to support multiprocessors, and that people have begun to investigate practical methods of removing the GIL (as opposed to just bitching about it for the sake of bitching). > The platitude that performance doesn't matter Who on earth says that? I've never heard anyone say that. What I've heard people say is that _machine_ performance isn't the only thing that needs to be maximized, or even the most important thing. Otherwise we'd all be writing hand-optimized assembly language, and there would be a waiting line of about five years to get access to the few programmers capable of writing that hand-optimized assembly language. > that programmer time is more valuable than machine time Programmer time is more valuable than machine time in many cases, especially when tasks are easily parallisable across many machines. That's why your "comparatively wimpy site" preferred to throw extra web servers at the job of serving webpages rather than investing in smarter, harder-working programmers to pull the last skerricks of performance out of the hardware you already had. > etc. is at best an excuse for laziness. What are you doing about solving the problem? Apart from standing on the side-lines calling out "Get yer lazy behinds movin', yer lazy bums!!!" at the people who aren't even convinced there is a problem that needs solving? > And more and more often, in the > application areas where Python is deployed, it's just plain wrong. Take > web servers: a big site like Google has something like a half million of > them. Even the comparatively wimpy site where I work has a couple > thousand. If each server uses 150 watts of power (plus air > conditioning), then if making the software 2x faster lets us shut down > 1000 of them, What on earth makes you think that would be anything more than a temporary, VERY temporary, shutdown? My prediction is that the last of the machines wouldn't have even been unplugged before management decided that running twice as fast, or servicing twice as many people at the same speed, is more important than saving on the electricity bill, and they'd be plugged back in. > the savings in electricity bills alone is larger than my > salary. Of course that doesn't include environmental benefits, hardware > and hosting costs, the costs and headaches of administering that many > boxes, etc. For a lot of Python users, significant speedups are a huge > win. Oh, I wouldn't say "No thanks!" to a Python speed up. My newest PC has a dual-core CPU (no cutting edge for me...) and while Python is faster on it than it was on my old PC, it isn't twice as fast. But Python speed ups don't come for free. For instance, I'd *really* object if Python ran twice as fast for users with a quad-core CPU, but twice as slow for users like me with only a dual-core CPU. I'd also object if the cost of Python running twice as fast was for the startup time to quadruple, because I already run a lot of small scripts where the time to launch the interpreter is a significant fraction of the total run time. If I wanted something like Java, that runs fast once it is started but takes a LONG time to actually start, I know where to find it. I'd also object if the cost of Python running twice as fast was for Guido and the rest of the Python-dev team to present me with their wages bill for six months of development. I'm grateful that somebody is paying their wages, but if I had to pay for it myself it wouldn't be done. It simply isn't that important to me (and even if it was, I couldn't afford it). Now there's a thought... given that Google: (1) has lots of money; (2) uses Python a lot; (3) already employs both Guido and (I think...) Alex Martelli and possibly other Python gurus; (4) is not shy in investing in Open Source projects; (5) and most importantly uses technologies that need to be used across multiple processors and multiple machines one wonders if Google's opinion of where core Python development needs to go is the same as your opinion? -- Steven. -- http://mail.python.org/mailman/listinfo/python-list
