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14000NM0001 K001 Supported log pages [0x0]: 0x00 Supported log pages [sp] 0x02 Write error [we] 0x03 Read error [re] 0x05 Verify error [ve] 0x06

=libaio, iodepth=32 fio-3.12 Starting 1 process Jobs: 1 (f=1): [w(1)][100.0%][w=1420KiB/s][w=355 IOPS][eta 00m:00s] test: (groupid=0, jobs=1): err= 0: pid=3377: Sat Jan 9 15:31:04 2021 write: IOPS=352, BW=1410Ki

values to f(x); each list item in l results in a separate job. Listing 1 Joblib: Embarrassingly Parallel 01 from joblib import Parallel, delayed 02 03 def f(x): 04 return x 05 06 l ... A Library for Many Jobs

a queue of pending work." These three points are the classic functions of a resource manager (job scheduler), and Slurm does them well. Slurm is very extensible, with more than 100 optional plugins ... One way to share HPC systems among several users is to use a software tool called a resource manager. Slurm, probably the most common job scheduler in use today, is open source, scalable, and easy ... Slurm Job Scheduling System

47 k pixman x86_64 0.38.4-2.el8 appstream 256 k slurm-contribs-ohpc x86_64 22.05.2-14.1.ohpc.2.6 OpenHPC-updates 22 k slurm

counter = 1,counter_limit 25 my_record%x = counter 26 my_record%y = counter + 1 27 my_record%z = counter + 2 28 my_record%value = counter * 10.0 29

04 address 192.168.0.100 05 check_command check-host-alive 06 contact_groups contacts 07 use check_5min_24x7

service downtimes: Listing 3 Alerting Rules 01 groups: 02 - name: Web application alerts 03 rules: 04 - alert: target_server root disk partion is getting full 05 expr: 100 - ((node_filesystem_avail_bytes{job

1084 image- store- 1299616369/image.manifest.xml admin available public x86_64 machine eki- F7901106 eri- 0C0D116C 05 IMAGE eki- F61410F1 image- store- 1299616170/kernel

.add(layers.BatchNormalization()) model.add(layers.Conv2D(64, (3,3), padding='same', activation='relu')) model.add(layers.BatchNormalization()) model.add(layers.MaxPooling2D(pool_size=(2,2))) model.add(layers.Dropout(0.5)) input