18%
10.04.2015
]
20 }
21 ]
22 }
23 ]
24 }
The script that performs the rsync operation, sync.sh, will look like Listing 3. Your script might be more complex (e.g., by adding some sort
18%
01.06.2024
is 20x because only 95 percent of the algorithm can execute in parallel (compute the fraction 1/20 from that 5% number). That limitation led to a search for embarrassingly parallel
algorithms
18%
30.11.2025
SUSE users should use the openSUSE Build Service to install [UCC:x20-kl-listing-bold]rabbit-mq[/UCC] http://3. Doing so means that YaST automatically adds repositories that you need later on.
Once you have
18%
07.11.2011
print str(id) + ' Total waste of CPU cycles!'
08
09 if '__main__' == __name__:
10
11 for i in xrange(20):
12 Process(target = waste, args = (i,)).start()
The counting.py
program delays
18%
30.11.2025
(number, label):
07 for i in xrange(number):
08 print ' ' + str(i) + ' ' + label
09 sleep((number - 15)/10.0)
10
11 if '__main__' == __name__:
12
13 p1 = Process(target = count, args = (20
18%
13.12.2018
_64 3/4
19 Verifying : bzip2-1.0.6-13.el7.x86_64 4/4
20
21 Installed:
22 mssql-server.x86_64 0:14.0.3026.27-2
23
24 Dependency
18%
30.11.2025
and arrival rate
19 $pdq::streams = pdq::CreateOpen($Workload, $ArrivalRate);
20 # Define the service rate for customers at the cash desk
21 pdq::SetDemand($ServerName, $Workload, $SeviceTime);
22
17%
17.06.2017
type for variable "a"
18 type(my_struct) :: a
19 ! ...
20 write(*,*) "i is ",a%i
21
22 ! Structures (variables) of the the derived type my_struct
23 type(my_struct) :: data
24 type
17%
05.08.2024
.Exit(1)
15 }
16
17 run(os.Args[1])
18 }
19
20 func row() {
21 for i := 0; i < size; i++ {
22 for j := 0; j < size; j++ {
23 array[i][j]++
24 }
25 }
26 }
27
28
17%
11.02.2016
19
20 mysql> CREATE TABLE `data_random` (
21 `id` CHAR(32) NOT NULL,
22 `data` VARCHAR(64) DEFAULT NULL,
23 `ts` TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
24
