warnings: new to list, first post, lmdb noob.

in one use case, caffe sequentially streams though >100GB lmdbs at a rate of ~30MB/s in blocks of about 40MB. however, if multiple caffe processes are reading the same lmdb (opened with MDB_RDONLY), read performance becomes limiting (i.e. the processes become IO bound), even though the disk has sufficient read bandwidth (say ~180MB/s). some of the relevant caffe lmdb code is here:

however, if i *both*
1) run  blockdev --setra 65536 --setfra 65536 /dev/sdwhatever

2) modify lmdb to call posix_madvise(env->me_map, env->me_mapsize, POSIX_MADV_SEQUENTIAL);

then i can get >1 reader to run without being IO limited.

for (2), see https://github.com/moskewcz/scratch/tree/lmdb_seq_read_opt

similarly, using a sequential read microbenchmark designed to model the caffe reads from here:

if i run one reader, i get 180MB/s bandwidth.

with two readers, but neither (1) nor (2) above, each gets ~30MB/s bandwidth.

with (1) and (2) enabled, and two readers, each gets ~90MB/s bandwidth.

any advice?

mwm

PS: backstory (skippable):

caffe originally used LevelDB to get better read performance for sequentially loading sets of ~1M 227x227x3 raw images (~200GB data). typically processing time is ~2 hours for this data set size, yielding a read BW need of 30MB/s or so. it's not really clear if/why LevelDB was uses aside from the fact that the caffe author was a google intern at the time he wrote it, but anecdotally i think the claim is that reading the raw .jpgs had perf. issues, although it's unclear exactly what or why. i guess it was the usual story about not getting sequential reads without using LevelDB. they switched to lmdb a while back.