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15%
Linux Local and Network Filesystems
07.01.2024
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 loop /snap/core22/864 loop15   7:15   0  12.3M  1 loop /snap/snap-store/959 loop16   7:16   0  73.9M  1 loop /snap/core22/817 loop17   7:17   0 349.7M  1 loop /snap/gnome-3-38-2004/140 loop18   7:18   0
15%
Predicting Drive Doom
20.10.2013
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: Z1F35P0G LU WWN Device Id: 5 000c50 050b954c3 Firmware Version: CC27 User Capacity: 3,000,592,982,016 bytes [3.00 TB] Sector Sizes: 512 bytes logical, 4096 bytes physical Device is: In smartctl
15%
Overview of cloud platforms and appliances
30.11.2025
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Athiphan Chunmano, 123RF
, your scaling options are virtually unlimited, and you can add Content Delivery Networks (CDN). As an example, SlideShare [1] integrates document downloads and Flash file hosting with Amazon S3 and Cloud
15%
Server virtualization with Citrix XenServer
04.08.2011
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{ 22 System.out.println("Expected arguments: [nfs server] [nfs path]"); 23 return; 24 } 25 26 Server server = new Server(args[0], args[1
15%
Small Tools for Managing HPC
18.10.2017
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-64/16.10/lib/libpgf90rtl.so (0x00007f5bc6516000)         libpgf90.so => /opt/pgi/linux86-64/16.10/lib/libpgf90.so (0x00007f5bc5f5f000)         libpgf90_rpm1.so => /opt/pgi/linux86-64/16.10/lib/libpgf90_rpm1.so
15%
Fast system management from Puppet Labs
30.11.2025
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© Artmann Witte, fotolia.com
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
15%
Resource Management with Slurm
05.11.2018
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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
15%
Resource Management with Slurm
13.12.2018
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Lead Image © Vladislav Kochelaevs, fotolia.com
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
15%
I/O benchmarks with Fio
30.11.2025
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© Kheng Ho Toh, 123RF.com
it took to process them (lat for latency.) Figure 1 shows the results of a test on a ThinkPad T520 with a 300GB Intel SSD 320 on kernel 3.0. When you are measuring performance, it makes sense to think
15%
High-performance Python – compiled code and C interface
01.08.2019
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Lead Image © Konrad Bak, 123RF.com
total x = numpy.arange(10_000_000); %time sum(x) CPU times: user 1.63 s, sys: 0 ns, total: 1.63 s Wall time: 1.63 s Next, add Numba into the code (Listing 2) so the @jit decorator can be used. (Don

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