20%
17.06.2017
-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))
Using forall, the same can be written as:
forall (i=2:n-1, j=2:n-1) a(i,j) = 0.25*(a(i-1,j) + a(i+1,j) + a(i,j-1) + a(i,j+1
20%
15.02.2012
rewinddir
0
0
0
0
0
0
0
0
fsync
21
21
21
21
21
22
26
31
lseekm
3
20%
26.01.2012
rewinddir
0
0
0
0
0
0
0
0
fsync
21
21
21
21
21
22
26
31
lseekm
3
20%
18.07.2013
rq2 ra92
08 set rq3 cdrom
09
10 attach rq0 d0.dsk
11 attach rq1 d1.dsk
12 attach rq2 d2.dsk
13
14 attach -r rq3 cdrom.iso
15
16 set rl disable
17 set ts disable
18
19 set xq mac=08-00-2B-AA-BB-CC
20
20%
09.10.2017
if page.get('Contents') is not None:
21 for file in page.get('Contents'):
22 s3pump(file.get('Key'), bucket)
Data Highway?
For large S3 buckets with data in the multiterabyte ... Data on AWS S3 is not necessarily stuck there. If you want your data back, you can siphon it out all at once with a little Python pump. ... Data Exchange with AWS S3 ... Getting data from AWS S3 via Python scripts
20%
10.11.2021
less compression but faster compression times and the default compression level being 3
. You can use compression levels 20
to 22
with an additional option. For even faster compression
20%
14.03.2013
: 0
16 initial apicid : 0
17 fdiv_bug : no
18 hlt_bug : no
19 f00f_bug : no
20 coma_bug : no
21 fpu : yes
22 fpu_exception : yes
23 cpuid level : 10
24 wp
20%
12.05.2020
.04"
],
"RepoDigests": [
"nvidia/cuda@sha256:3cb86d1437161ef6998c4a681f2ca4150368946cc8e09c5e5178e3598110539f"
],
"Parent": "",
"Comment": "",
"Created": "2019-11-27T20:00
20%
02.08.2022
docker-compose.yaml
version: '3'
services:
target1:
build: .
ports:
- '3000:80'
- '2000:22'
container_name: target1
target2:
build
20%
05.02.2019
', 'makecache'] with allowed return codes [0] (shell=False, capture=False)
...
2018-10-17 22:00:06,125 - util.py[DEBUG]: Running command ['yum', '-t', '-y', 'upgrade'] with allowed return codes [0] (shell
