29%
07.06.2019
application in a fast key value store such as Redis [1], from which the web application then retrieves it.
You can also work with HTTP caching [2]. The web application tells the web browser that the currently
29%
04.08.2020
what you could expect when you've connected different types of devices. Stethoscope can pull endpoint data from a number of different device information and management systems, including Jamf [2
29%
07.03.2019
...
end do
#pragma acc parallel loop collapse(2)
{
for (i=0, i < n, i++) {
...
for (j=0; j < m; j++) {
...
}
...
}
}
If the loops cannot
29%
12.09.2022
= np.random.rand(nx,ny)*100.0 # Random data in arrayy
np.save(filename, a) # Write data to file
print(" Just finished writing file, ",filename,".npy")
# end for
The code in Listing 2 reads the five files
29%
05.12.2016
} ${TABLENAME} -nL ${CHAINNAME} 2> /dev/null 1> /dev/null
048 RET=$?
049 return ${RET}
050 fi
051 }
052
053 function delete_rule
054 {
055 # Find correct rule parameters
056 RULE=`echo ${@} | awk
29%
21.08.2014
MIPS : 1993.93
17 processor : 2
18 BogoMIPS : 1993.93
19 processor : 3
20 BogoMIPS : 1993.93
21 Features : swp half thumb fastmult vfp edsp neon vfpv3 tls
22 CPU implementer : 0
29%
15.12.2016
are over i
= 2,n
− 1 and j
= 2,n
−1. Here is how you can write the iteration over the domain using array notation:
a(2:n-1,2:n-1) = 0.25 * &
(a(1:n-2,2:n) + a(3:n,2:n) + a(2:n,1:n-2) + a(2:n,3:n ... Modern Fortran – Part 2
29%
25.01.2017
) :: a[*] ! Array coarray
real, dimension(n), codimension[*] :: a ! Array coarray
integer :: cx[10,10,*] ! scalar coarray with corank of 3
! Array coarray with corank of 3 with different cobounds
real :: c(m,n) :: [0
29%
20.02.2023
=/etc/slurm/slurm.epilog.clean
NodeName=n0001 Sockets=1 CoresPerSocket=4 ThreadsPerCore=2 State=UNKNOWN
PartitionName=normal Nodes=ALL Default=YES MaxTime=24:00:00 State=UP Oversubscribe=EXCLUSIVE
Slurmctld
29%
17.07.2023
install -c conda-forge -y cudatoolkit=11.8.0
# Tensorflow:
conda install -c conda-forge -y cudatoolkit=11.8.0
python3 -m pip install nvidia-cudnn-cu11==8.6.0.163 tensorflow==2.12.*
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
echo 'CUDNN
