23%
20.11.2013
10 10:00 lost+found
4 -rw-r--r-- 1 root root 294 Nov 10 10:07 s3ql_passphrase
4 -rw-r--r-- 1 root root 243 Nov 10 10:07 s3ql_seq_no_1
4 drwxr-xr-x. 4 root root 4096 Nov 10 10:08 ..
4 -rw-r--r-- 1
23%
07.06.2019
-jdk-alpine
02
03 RUN apk add --no-cache git openssh-client curl bash # for Jenkins AWT
04 ttf-dejavu
05
06 ARG JENKINS_USER=jenkins
07 ARG UID=1000
08 ARG HTTP_PORT=8080
09 ARG JENKINS
23%
21.11.2012
_get_num_threads()
04
05 !$OMP PARALLEL PRIVATE (id)
06
07 id = omp_get_thread_num()
08 write(*,*) 'Thread ',id,' Checking in'
09
10 IF (id == 0) THEN
11 WRITE(*,*) ' Number of threads in use is ',omp
23%
13.10.2020
the asymptote is the inverse of the serial portion of the code, which controls the scalability of the application
. In this example, p
= 0.8 and (1 – p
) = 0.2, so the asymptotic value is a
= 5.
Further
23%
02.02.2021
. That means the serial portion is 1 - p
, so the asymptote is the inverse of the serial portion of the code, which controls the scalability of the application
. In this example, p
= 0.8 and (1 - p
) = 0.2, so
23%
12.09.2013
;
05
06 print "Status: 200\nContent-Type: text/plain\n\n";
07 $|=1; $|=0; # flush
08
09 my $dbh=DBI->connect('dbi:Pg:dbname=r2', 'ipp', undef, {RaiseError=>1});
10
11 my $sth
23%
16.08.2018
| nova | compute |
| 266b6275884945d39dbc08cb3297eaa2 | ceilometer | metering |
| 4f0ebe86b6284fb689387bbc3212f9f5 | cinder | volume |
| 59392edd44984143bc47a89e111beb0a
23%
17.06.2017
03 REAL, ALLOCATABLE :: a(:,:)
04 INTEGER :: n
05 INTEGER :: allocate_status
06 n=1000
07 ALLOCATE( a(n,n), STAT = allocate_status)
08 IF (allocate_status /= 0) STOP "Could not allocate
23%
02.06.2020
--upgrade pip
pip install --upgrade tensorflow=2.0 pandas numpy pathlib
## Check the setup
python -c "import tensorflow as tf;print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
Neural Network
23%
18.07.2013
), 0 (write only)
1024KB, 64KB, 8KB, 4KB, 512 bytes
Sequential write with 1024KB block size
Latency
Random: 100, 65, 08
8KB, 4KB, 512 bytes
Random write with 4KB
