Glen Lenker wrote: > On Thu, Mar 26, 2009 at 09:50:08PM +0000, Ralf Wildenhues wrote: >> Hi Paul, all, >> >> Paul Eggert writes: >> > >> > This patch is by Glen Lenker, Matt Pham, Benjamin Nuernberger, Sky >> > Lin, TaeSung Roh, and Paul Eggert. It adds support for parallelism >> > within an internal sort. On our simple tests on a 2-core desktop x86, >> > overall performance improved by roughly a factor of 1.6. >> >> This is too interesting to pass up. >> >> Example run, on an 8-way, and with cat'ed instances of the dictionary, >> on tmpfs, timings best of three: > > Hey Ralf, did you happen to specify the amount of RAM sort should > use. Not specifying enough RAM for sort would force break what would > be a single internal sort into multiple internal sort passes and then > an external sort. As it is external sort is still sequential. > >> runtime [s] threads >> file size [MB] 1 2 4 8 >> 1 0.06 0.04 0.03 0.04 >> 2 0.13 0.09 0.07 0.07 >> 4 0.28 0.20 0.16 0.15 >> 8 0.61 0.43 0.34 0.32 >> 16 1.34 0.94 0.74 0.72 >> 32 3.00 2.06 1.63 1.57 >> 64 6.36 4.38 3.44 3.32 >> 128 13.49 9.30 7.13 7.24 >> 256 28.62 19.49 15.17 15.18 > > I ran these tests on a 256MB instance of the dictionary in tmpfs, on a > 8-core machine specifying 2G of RAM. > > runtime [s] threads > file size [MB] 1 2 4 8 > 256 2m41.219 1m27.357 52.53 36.429 > >> Here's the abbreviated 'time' output for the last row: >> >> 26.95user 1.67system 0:28.62elapsed 100%CPU >> 30.78user 1.98system 0:19.49elapsed 168%CPU >> 37.41user 2.04system 0:15.17elapsed 260%CPU >> 60.68user 2.79system 0:15.18elapsed 417%CPU > > I forgot to use your time format in the test above, this is from a > seperate test run. > > 160.22user 1.34system 2:41.61elapsed 99%CPU > 159.83user 1.45system 1:27.12elapsed 185%CPU > 159.84user 1.56system 0:52.26elapsed 308%CPU > 160.67user 1.53system 0:36.26elapsed 447%CPU > > This seems to be what I would expect from a good implementation. > >> It suggests to me that too much time is spent busy-waiting in pthread_join, >> or that sort is computing too much (I haven't looked at the patch in detail). >> >> Also, I'd have expected the rate going from 1 to 2 threads to get at least >> a bit better with bigger file size, but it remains remarkably constant, >> around 1.45 for this setup. What am I missing?
Hi Glen, I ran some tests (see below), and got results that look similar to Ralf's. I used an otherwise-idle 16-core Nehalem-based system with 8GB of RAM. However, more importantly, while the 16- and 8-thread tests were running, I sampled thread counts using ps and was surprised to see the number of active threads was usually far less than the maximum. First the data: cat /usr/share/dict/words > k n=$(echo '250*1024^2 / '$(wc -c < k)|bc -l|sed 's/\..*//') n=$(expr $n + 1) # Create a file of size ~250MB : > in; for i in $(seq $n); do echo $i; shuf k >> in; done $ du -sh in : 251M in for t in 16 8 4 2 1; do echo T=$t for i in 1 2 3 4; do env time --format %e sort --threads=$t --buffer-size=2G < in > /dev/null done done T=16 T is number of threads 12.96 <--- This is elapsed wall-clock time in seconds. 16.43 13.76 16.60 T=8 18.44 18.53 18.30 18.19 T=4 20.82 20.86 21.17 20.72 T=2 28.15 28.25 28.33 28.16 T=1 43.36 43.43 35.09 43.42 Running it again: T=16 16.53 13.54 13.87 16.79 T=8 16.82 18.23 18.07 18.35 T=4 22.86 22.59 22.62 20.72 T=2 28.22 28.27 28.24 28.22 T=1 43.29 35.10 43.32 35.04 ======================================== Then, I reran the 16-thread tests like this in one window $ for t in 16; do : echo T=$t for i in 1 2 3 4; do env time --format %e sort --threads=$t --buffer-size=500M < in > /dev/null done done while recording sort thread counts in another with this: for i in $(seq 1600); do n=$(env ps -C sort -o nlwp=) date "+%s.%N $n"; sleep .05 done | tee log The timings are much like the ones above, T=16 15.92 14.75 16.76 16.68 but the thread counts are surprising: (I started the thread-counter slightly before the sort commands) 1243538765.058470000 1243538765.143037000 1243538765.226945000 1243538765.310864000 1243538765.395248000 1243538765.478934000 1243538765.562841000 1243538765.650482000 1243538765.734979000 1243538765.818997000 1243538765.903010000 1243538765.986913000 1243538766.071028000 1243538766.156459000 1243538766.240510000 1 1243538766.312877000 1 1243538766.384981000 1 1243538766.456768000 1 1243538766.528718000 1 1243538766.601155000 1 1243538766.672983000 1 1243538766.745109000 1 1243538766.817065000 1 1243538766.940538000 16 1243538767.091641000 16 1243538767.235828000 16 1243538767.333629000 12 1243538767.405164000 8 1243538767.484498000 6 1243538767.571476000 4 1243538767.648512000 4 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