1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
|
tcpp -- Parallel TCP Exercise Tool
This is a new tool, and is rife with bugs. However, it appears to create
even more problems for device drivers and the kernel, so that's OK.
This tool generates large numbers of TCP connections and stuffs lots of data
into them. One binary encapsulates both a client and a server. Each of the
client and the server generates a certain number of worker processes, each of
which in turn uses its own TCP port. The number of server processes must be
>= the number of client processes, or some of the ports required by the
client won't have a listener. The client then proceeds to make connections
and send data to the server. Each worker multiplexes many connections at
once, up to a maximum parallelism limit. The client can use one or many IP
addresses, in order to make more 4-tuples available for testing, and will
automatically spread the load of new connections across available source
addresses.
You will need to retune your TCP stack for high volume, see Configuration
Notes below.
The server has very little to configure, use the following command line
flags:
-s Select server mode
-p <numprocs> Number of workers, should be >= client -p arg
-r <baseport> Non-default base TCP port, should match client
-T Print CPU usage every ten seconds
-m <maxconnectionsperproc> Maximum simultaneous connections/proc, should
be >= client setting.
Typical use:
./tcpp -s -p 4 -m 1000000
This selects server mode, four workers, and at most 1 million TCP connections
per worker at a time.
The client has more to configure, with the following flags:
-c <remoteIP> Select client mode, and specific dest IP
-C Print connections/second instead of GBps
-P Pin each worker to a CPU
-M <localIPcount> Number of sequential local IPs to use; req. -l
-T Include CPU use summary in stats at end of run
-b <bytespertcp> Data bytes per connection
-l <localIPbase> Starting local IP address to bind
-m <maxtcpsatonce> Max simultaneous conn/worker (see server -m)
-p <numprocs> Number of workers, should be <= server -p
-r <baseport> Non-default base TCP port, should match server
-t <tcpsperproc> How many connections to use per worker
Typical use:
./tcpp -c 192.168.100.201 -p 4 -t 100000 -m 10000 -b 100000 \
-l 192.168.100.101 -M 4
This creates four workers, each of which will (over its lifetime) set up and
use 100,000 TCP connections carrying 100K of data, up to 10,000 simultaneous
connection at any given moment. tcpp will use four source IP addresses,
starting with 192.168.100.101, and all connections will be to the single
destination IP of 192.168.100.201.
Having (p) <= the number of cores is advisable. When multiple IPs are used
on the client, they will be sequential starting with the localIPbase set with
-l.
Known Issues
------------
The bandwidth estimate doesn't handle failures well. It also has serious
rounding errors and probably conceptual problems.
It's not clear that kevent() is "fair" to multiple connections.
Rather than passing the length for each connection, we might want to pass
it once with a control connection up front. On the other hand, the server
is quite dumb right now, so we could take advantage of this to do size
mixes.
Configuration Notes
-------------------
In my testing, I use loader.conf entries of:
kern.ipc.maxsockets=1000000
net.inet.tcp.maxtcptw=3000000
kern.ipc.somaxconn=49152
kern.ipc.nmbjumbo16=262144
kern.ipc.nmbjumbo9=262144
kern.ipc.nmbjumbop=262144
kern.ipc.nmbclusters=262144
net.inet.tcp.syncache.cachelimit=65536
net.inet.tcp.syncache.bucketlimit=512
# May be useful if you can't use multiple IP addresses
net.inet.ip.portrange.first=100
# For running !multiq, do this before loading the driver:
kenv hw.cxgb.singleq="1"
kldload if_cxgb
# Consider turning off TSO and/or adjusting the MTU for some scenarios:
ifconfig cxgb0 -tso
ifconfig cxgb0 mtu 1500
|
