22%
04.10.2018
employees; with 20 help desk employees, it costs around $2,800. Prices in other currencies are available on request. The "Free Edition" for managing a maximum of 100 AD objects in a single domain is free
22%
18.07.2013
-Code of the IOPS Tests
01 Make Secure Erase
02 Workload Ind. Preconditioning
03 While not steady state
04 For workloads [100, 95, 65, 50, 35, 5, 0]
05 For block sizes ['1024k', '128k', '64k', '32k
22%
17.05.2017
_ACC_RDWR_F, FILE_ID, IERR, PLIST_ID)
96
97 ! Close the property list
98 CALL h5pclose_f(PLIST_ID, IERR)
99
100 ! Create the dataset names based on MPI rank
101 WRITE(C,"(i0)") MPI_RANK + 1
102 DATASET
22%
23.01.2012
was approximately 300MB, and just under 100MB for the temporary staging space.
Keep the temporary staging directory intact for future installations and customizations. The disk cost for these files is minimal
22%
13.02.2017
/CIS_Docker_1.11.0_Benchmark_v1.0.0.pdf
AppArmor: http://wiki.apparmor.net/index.php/Main_Page
Grsecurity: https://grsecurity.net
PaX: https://pax.grsecurity.net
Docker capabilities allowed
22%
28.11.2023
and install the VS Code Server component into the target Linux environment. This footprint, well beyond 100MB, represents the runtime software for Visual Code Server. From the SSH remoting scenario, you can
22%
05.02.2019
% compatible anymore. When it comes to switching, you need to be on your toes!
MariaDB v5.5 was followed by version 10.0. This version leap should have made it clear that MariaDB was already a bit different
22%
21.03.2017
# ===================
09 #
10 if __name__ == '__main__':
11
12 f = h5py.File("mytestfile.hdf5", "w")
13
14 dset = f.create_dataset("mydataset", (100,), dtype='i')
15
16 dset[...] = np.arange(100)
17
22%
18.02.2018
command writes CPU stats to standard output (stdout) for each available processor in the node, starting with CPU 0. It reports a boatload of statistics, including:
CPU: Processor number for the output
22%
19.06.2023
a = 100.0*np.random.random((N,N))
a.astype(np.float64)
print("a[5,5] = ",a[5,5]," type = ",a[5,5].dtype)
np.save('double', a)
b = np.copy(a)
b = b.astype(np.float32)
print("b[5,5] = ",b[5,5]," type = ",b[5
