24%
12.02.2013
in to another node (n0
in this case). On the first login, the modules are loaded on the remote node. On the second login, with NOMODULES
set, no modules are available:
$ module list
Currently Loaded
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16.05.2013
in Listing 2, in which two modules are loaded (fftw and mpich2) before logging in to another node (n0 in this case). On the first login, the modules are loaded on the remote node. On the second login
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04.04.2023
.
For practical use, you first need to call kinit with the -n option to give you an anonymous TGT:
kinit -n
klist
Ticket cache: KCM:0
Default principal: WELLKNOWN/ANONYMOUS@WELLKNOWN:ANONYMOUS
[...]
You can now
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02.08.2022
._tcp.mykier.ip,ipa.mykier.ip,389
A Berkeley Internet Name Domain (BIND) 9 DNS server needs the same entries, but in a different format:
_kerberos._udp.mykier.ip. 86400 IN SRV 0 100 88 ipa.mykier.ip.
[...]
The important
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05.12.2014
_domain": "yourdomain.com",
06 "dataset_uuid": "d34c301e-10c3-11e4-9b79-5f67ca448df0",
07 "resolvers": [
08 "192.128.0.9",
09 "192.128.0.10"
10 ],
11 "max_physical_memory": 4096,
12 "nics": [
13
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15.04.2013
.1, do not improve on this; it is not until TLS 1.2 that TLS began to support newer algorithms with SHA-2.
On the server side, you need version 1.0.1 of OpenSSL to enable TLS 1.2, for example
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20.08.2012
the port after the file transfer has completed (but not without moving to the netcat-traditional
package, as mentioned before):
{ echo -ne "HTTP/1.0 200 OK\r\n\r\n"; cat filename.tar.gz; } | nc -l -p 15000
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02.08.2022
.
Listing 1
Samsara Syntax Examples
val G = B %*% B.t - C - C.t + (xi dot xi) * (s_q cross s_q)
// Dense vectors:
val denseVec1: Vector = (1.0, 1.1, 1.2)
val denseVec2 = dvec(1, 0, 1, 1, 1, 2
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11.06.2014
/joe/.ssh/google_compute_engine -A -p 22 joe@1.2.3.4 --
11 Warning: Permanently added '1.2.3.4' (ECDSA) to the list of known hosts.
12 Enter passphrase for key '/home/joe/.ssh/google_compute_engine':
13 Linux gcerocks-instance-1 3.2.0
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02.06.2020
optimizer = tf.keras.optimizers.RMSprop(0.001)
11 model.compile(loss='mean_squared_error',
12 optimizer=optimizer,
13 metrics=['mean_absolute_error', 'mean_squared_error'])
The model is shown
