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+Some basic notes on performance:
+
+## Memory Footprint
+
+The [MemoryFootprint](MemoryFootprint) page has more specific information.
+
+The
+[graph](http://allmydata.org/tahoe-figleaf-graph/hanford.allmydata.com-tahoe_memstats.html)
+munin shows our static memory footprint (starting a node but not doing
+anything with it) to be about 24MB. Uploading one file at a time gets the
+node to about 29MB. (we only process one segment at a time, so peak memory
+consumption occurs when the file is a few MB in size and does not grow beyond
+that). Uploading multiple files at once would increase this.
+
+## Network Speed
+
+### test results
+
+Using a 3-server testnet in colo and an uploading node at home (on a DSL line
+that gets about 150kBps upstream and has a 14ms ping time to colo) using
+0.5.1-34 takes 820ms-900ms per 1kB file uploaded (80-90s for 100 files, 819s
+for 1000 files).
+
+'scp' of 3.3kB files (simulating expansion) takes 8.3s for 100 files and 79s
+for 1000 files, 80ms each.
+
+Doing the same uploads locally on my laptop (both the uploading node and the
+storage nodes are local) takes 46s for 100 1kB files and 369s for 1000 files.
+
+
+
+### Roundtrips
+
+The 0.5.1 release requires about 9 roundtrips for each share it uploads. The
+upload algorithm sends data to all shareholders in parallel, but these 9
+phases are done sequentially. The phases are:
+
+ 1. allocate_buckets
+ 1. send_subshare (once per segment)
+ 1. send_plaintext_hash_tree
+ 1. send_crypttext_hash_tree
+ 1. send_subshare_hash_trees
+ 1. send_share_hash_trees
+ 1. send_UEB
+ 1. close
+ 1. dirnode update
+
+We need to keep the send_subshare calls sequential (to keep our memory
+footprint down), and we need a barrier between the close and the dirnode
+update (for robustness and clarity), but the others could be pipelined.
+9*14ms=126ms, which accounts for about 15% of the measured upload time.
+
+## Storage Servers
+
+ext3 (on tahoebs1) refuses to create more than 32000 subdirectories in a
+single parent directory. In 0.5.1, this appears as a limit on the number of
+buckets (one per storage index) that any [StorageServer](StorageServer) can hold. A simple
+nested directory structure will work around this.. the following code would
+let us manage 33.5G shares:
+
+```
+  from idlib import b2a
+  os.path.join(b2a(si[:2]), b2a(si[2:4]), b2a(si))
+```
+
+This limitation is independent of problems of memory use and lookup speed.
+Once the number of buckets is large, the filesystem may take a long time (and
+multiple disk seeks) to determine if a bucket is present or not. The
+provisioning page suggests how frequently these lookups will take place, and
+we can compare this against the time each one will take to see if we can keep
+up or not. If and when necessary, we'll move to a more sophisticated storage
+server design (perhaps with a database to locate shares).