21%
04.08.2020
(minified by 25.99X)
from python:2.7-alpine - 84.3MB => 23.1MB (minified by 3.65X)
from python:2.7.15 - 916MB => 27.5MB (minified by 33.29X)
from centos:7 - 647MB => 23MB (minified by 28.57X)
from centos
21%
30.11.2025
is capable of executing jobs at a very high speed. I have used the framework in an environment with more than 3,000 systems; running a job on all of the nodes rarely took more than 30 seconds.
YAML
21%
05.11.2018
it the number of cores, number of cores per socket, threads per core, and the amount of memory available (e.g., 30,000MB, or 30GB, here).
CgroupAutomount=yes
CgroupReleaseAgentDir="/etc/slurm/cgroup"
Constrain
21%
13.12.2018
socket, threads per core, and the amount of memory available (e.g., 30,000MB, or 30GB, here).
CgroupAutomount=yes
CgroupReleaseAgentDir="/etc/slurm/cgroup"
ConstrainCores=yes
Constrain
21%
25.03.2020
, according to the README file, requires "half the memory, all in a binary less than 40MB" to run. By design, it is authored with a healthy degree of foresight by the people at Rancher [3]. The GitHub page [4 ... The k3s lightweight and secure Kubernetes distribution can handle both unattended workloads in remote locations with minimal resources and clusters of IoT appliances. ... Kubernetes k3s lightweight distro
21%
05.03.2014
tool.
Enter GlusterFS (Figures 3 and 4).
Figure 3: Internally, RHSS relies on Gluster software, and you can use many Gluster commands for storage
21%
09.10.2017
boto3
3
4 s3 = boto3.resource('s3')
5 bucket = s3.Bucket('prosnapshot')
6 bucket.download_file('hello.txt', 'hello-down.txt')
Figure 2 ... 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
21%
30.01.2024
Dell Precision Workstation T7910
Power
1,300W
CPU
2x Intel Xeon Gold E5-2699 V4, 22 cores, 2.4GHz, 55MB of cache, LGA 2011-3
GPU, NPU
n/a*
Memory
21%
14.11.2013
. This translates to Google's experiencing about 25,000-75,000 correctable errors (CE) per billion device hours per megabit, which translates to 2,000-6,000 CE/GB-yr (or about 250-750 CE/Gb-yr). This is much higher
21%
04.08.2020
, repeating the measurement 100,000 times leads to an approximate time measurement of 6ns for the round n
Figure 4: Bench testing round() in C: 6.23ns fast
