26%
17.06.2017
integer :: allocate_status
08 !
09 n = 10
10 allocate( array(n, n), stat = allocate_status )
11 if (allocate_status /= 0) stop "Could not allocate array"
12 !
13 subarray => array(3:7,3:7)
14
26%
02.08.2021
.196418
1.575951
87.21019
3.468651
39.623174
8,192
39.343849
27.946214
102.974144
10.677551
12.247917
89.771315
26.561623
41
25%
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
25%
16.03.2021
=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
25%
10.04.2015
the patch for kernel versions 3.18 and 3.19.x [17]. If you are uncertain as to how to proceed, you can either look for help on the Internet or check out Julian Kirsch's [12] master's thesis. You will find
25%
12.09.2013
=$dbh->prepare('select burncpu(?)');
12 $sth->execute((($ENV{QUERY_STRING}+0) || .5).'s');
13
14 while( my $row=$sth->fetchrow_arrayref ) {
15 print "@$row\n";
16 }
Workaround
The script is simple, but the attentive
25%
06.10.2019
);
19 printf("source: %s\ntarget: %s\n",source,target);
20 return 0;
21 }
Figure 3: Splint warns the programmer of a likely out
25%
09.04.2019
unexplained delays of a few seconds while renaming some gigabyte-sized files [2] on a fast cloud instance [3]. I was able to reproduce his result in an AWS EC2 m5d.large instance running Ubuntu Server 18
25%
09.10.2023
12 7:12 0 40.8M 1 loop /snap/snapd/20092
sda 8:0 0 5.5T 0 disk
|---sda1 8:1 0 5.5T 0 part /home2
nvme1n1 259:0 0 953.9G 0 disk
|---nvme1n1p1
25%
01.06.2024
the same test with a 44-million sample test,
time mpiexec -n 44 mpiPI-44M
Figure 4: btop [12] visualizing CPU core activations
