tree 058e169e06f14dee643c26b0a9ef7bcb82fad73f
parent e9e8adf1a871d22d9df7498256681685459b2507
author Matheus Tavares <matheus.bernardino@usp.br> 1618791295 -0300
committer Junio C Hamano <gitster@pobox.com> 1618858625 -0700

parallel-checkout: add configuration options

Make parallel checkout configurable by introducing two new settings:
checkout.workers and checkout.thresholdForParallelism. The first defines
the number of workers (where one means sequential checkout), and the
second defines the minimum number of entries to attempt parallel
checkout.

To decide the default value for checkout.workers, the parallel version
was benchmarked during three operations in the linux repo, with cold
cache: cloning v5.8, checking out v5.8 from v2.6.15 (checkout I) and
checking out v5.8 from v5.7 (checkout II). The four tables below show
the mean run times and standard deviations for 5 runs in: a local file
system on SSD, a local file system on HDD, a Linux NFS server, and
Amazon EFS (all on Linux). Each parallel checkout test was executed with
the number of workers that brings the best overall results in that
environment.

Local SSD:
             Sequential             10 workers            Speedup
Clone        8.805 s ± 0.043 s      3.564 s ± 0.041 s     2.47 ± 0.03
Checkout I   9.678 s ± 0.057 s      4.486 s ± 0.050 s     2.16 ± 0.03
Checkout II  5.034 s ± 0.072 s      3.021 s ± 0.038 s     1.67 ± 0.03

Local HDD:
             Sequential             10 workers             Speedup
Clone        32.288 s ± 0.580 s     30.724 s ± 0.522 s    1.05 ± 0.03
Checkout I   54.172 s ±  7.119 s    54.429 s ± 6.738 s    1.00 ± 0.18
Checkout II  40.465 s ± 2.402 s     38.682 s ± 1.365 s    1.05 ± 0.07

Linux NFS server (v4.1, on EBS, single availability zone):

             Sequential             32 workers            Speedup
Clone        240.368 s ± 6.347 s    57.349 s ± 0.870 s    4.19 ± 0.13
Checkout I   242.862 s ± 2.215 s    58.700 s ± 0.904 s    4.14 ± 0.07
Checkout II  65.751 s ± 1.577 s     23.820 s ± 0.407 s    2.76 ± 0.08

EFS (v4.1, replicated over multiple availability zones):

             Sequential             32 workers            Speedup
Clone        922.321 s ± 2.274 s    210.453 s ± 3.412 s   4.38 ± 0.07
Checkout I   1011.300 s ± 7.346 s   297.828 s ± 0.964 s   3.40 ± 0.03
Checkout II  294.104 s ± 1.836 s    126.017 s ± 1.190 s   2.33 ± 0.03

The above benchmarks show that parallel checkout is most effective on
repositories located on an SSD or over a distributed file system. For
local file systems on spinning disks, and/or older machines, the
parallelism does not always bring a good performance. For this reason,
the default value for checkout.workers is one, a.k.a. sequential
checkout.

To decide the default value for checkout.thresholdForParallelism,
another benchmark was executed in the "Local SSD" setup, where parallel
checkout showed to be beneficial. This time, we compared the runtime of
a `git checkout -f`, with and without parallelism, after randomly
removing an increasing number of files from the Linux working tree. The
"sequential fallback" column below corresponds to the executions where
checkout.workers was 10 but checkout.thresholdForParallelism was equal
to the number of to-be-updated files plus one (so that we end up writing
sequentially). Each test case was sampled 15 times, and each sample had
a randomly different set of files removed. Here are the results:

             sequential fallback   10 workers           speedup
10   files    772.3 ms ± 12.6 ms   769.0 ms ± 13.6 ms   1.00 ± 0.02
20   files    780.5 ms ± 15.8 ms   775.2 ms ±  9.2 ms   1.01 ± 0.02
50   files    806.2 ms ± 13.8 ms   767.4 ms ±  8.5 ms   1.05 ± 0.02
100  files    833.7 ms ± 21.4 ms   750.5 ms ± 16.8 ms   1.11 ± 0.04
200  files    897.6 ms ± 30.9 ms   730.5 ms ± 14.7 ms   1.23 ± 0.05
500  files   1035.4 ms ± 48.0 ms   677.1 ms ± 22.3 ms   1.53 ± 0.09
1000 files   1244.6 ms ± 35.6 ms   654.0 ms ± 38.3 ms   1.90 ± 0.12
2000 files   1488.8 ms ± 53.4 ms   658.8 ms ± 23.8 ms   2.26 ± 0.12

From the above numbers, 100 files seems to be a reasonable default value
for the threshold setting.

Note: Up to 1000 files, we observe a drop in the execution time of the
parallel code with an increase in the number of files. This is a rather
odd behavior, but it was observed in multiple repetitions. Above 1000
files, the execution time increases according to the number of files, as
one would expect.

About the test environments: Local SSD tests were executed on an
i7-7700HQ (4 cores with hyper-threading) running Manjaro Linux. Local
HDD tests were executed on an Intel(R) Xeon(R) E3-1230 (also 4 cores
with hyper-threading), HDD Seagate Barracuda 7200.14 SATA 3.1, running
Debian. NFS and EFS tests were executed on an Amazon EC2 c5n.xlarge
instance, with 4 vCPUs. The Linux NFS server was running on a m6g.large
instance with 2 vCPUSs and a 1 TB EBS GP2 volume. Before each timing,
the linux repository was removed (or checked out back to its previous
state), and `sync && sysctl vm.drop_caches=3` was executed.

Co-authored-by: Jeff Hostetler <jeffhost@microsoft.com>
Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br>
Signed-off-by: Junio C Hamano <gitster@pobox.com>