Scalable memory allocation using jemalloc

I'm impressed that there is still room to eke performance improvements out by fiddling with the base data structure, the original author has been working on refining it for quite a while*<p>* <a href="http://t-t-travails.blogspot.com/2008/07/treaps-versus-red-black-trees.html" rel="nofollow">http://t-t-travails.blogspot.com/2008/07/treaps-versus-red-b...</a>, <a href="http://t-t-travails.blogspot.com/2010/04/red-black-trees-revisited.html" rel="nofollow">http://t-t-travails.blogspot.com/2010/04/red-black-trees-rev...</a>

40 points and no comments?<p>Just wanted to say it is great submissions like this that make me come to Hacker News...<p>Thank you for taking the time to write this up and post it here...

YMMV but for my Python web app executing mostly OO Python 2.5.x code, I got a 10% performance increase by using jemalloc compared to the malloc in RHEL 5. It's as simply as LD_PRELOAD=/path/to/libjemalloc.so -- memory usage is also better (millions of objects allocated than eventually released in a long running process ended up with smaller amount of memory used when using jemalloc).

It would be interesting to see a performance comparison with nedmalloc. It uses a trie instead a of redblack-tree for a faster information access.<p><a href="http://www.nedprod.com/programs/portable/nedmalloc/" rel="nofollow">http://www.nedprod.com/programs/portable/nedmalloc/</a><p>Some time ago I evaluated both of them, and they seemed the best available choices. But I never found a comparison study.

Why is this not the default malloc shipped with libc's around the world yet?