On 03/12/2017 09:11 PM, Dan Eloff wrote:
Two things about this surprised me greatly:
1) That batching function calls using futures like this, with the
effect of a hot icache and slightly cooler dcache in just a few parts
of ScyllaDB led to a 50% speedup. I would have never thought it would
make such a difference.
I was just as surprised.
2) Your codebase was already using futures, so the changes to ScyllaDB
itself were minimal. Very nicely done.
I will keep this technique, and Seastar itself, in mind for future
applications. Thanks for sharing!
On Thu, Mar 9, 2017 at 8:41 AM, Avi Kivity <[email protected]
<mailto:[email protected]>> wrote:
We noticed in ScyllaDB that performance suffers due to high icache
miss rate; we saw a very low IPC.
We implemented a SEDA-like mechanism to run tasks tied to the same
function sequentially; the first task warms up icache and the
branch predictors, the second and further runs benefit from this
warmup.
The implementation of the mechanism in seastar can be viewed here:
https://github.com/scylladb/seastar/commit/384c81ba7227a9a99d485d1bb68c98c5f3a6b209
<https://github.com/scylladb/seastar/commit/384c81ba7227a9a99d485d1bb68c98c5f3a6b209>
Usage in ScyllaDB, with some performance numbers, can be viewed
here:
https://github.com/scylladb/scylla/commit/efd96a448cca4499fd40df8b3df3f0f8444a1464
<https://github.com/scylladb/scylla/commit/efd96a448cca4499fd40df8b3df3f0f8444a1464>.
Microbenchmarks see almost 200% improvement while full-system
tests see around 50% improvement, mostly due to improved IPC.
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