18%
10.04.2015
getsockopt ...
17 Resolving symbol close ...
18 Resolving symbol epoll_wait ...
19 Resolving symbol select ...
20 All dynamic symbols could be resolved.
21 socket(2, 1, 6) = 3
22 Socket 3 will be Knockified
18%
07.10.2014
_string;
08
09 static int prochello_show( struct seq_file *m, void *v )
10 {
11 int error = 0;
12
13 error = seq_printf( m, "%s\n", output_string);
14 return error;
15 }
16
17 static int prochello
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09.01.2013
source products, such as OpenStack [1], openQRM [2], Eucalyptus [3], or Ganeti [4], each with its specific functionality and concepts.
Because of the diversity of scenarios, most cloud stacks behave
18%
02.08.2021
in increased performance.
Octave
Probably one of the best examples I know for the use of the LD_PRELOAD trick is to push basic linear algebra subprogram (BLAS) [3] computations from a CPU onto an NVidia GPU. I
18%
13.06.2022
) for a class B problem size.
Therefore, I will run the EP, FT, and MG tests to check health performance. For class B, the EP test takes 5.46s, the FT test 17.26s, and the MB test 3.8s. If I stay with only
18%
26.01.2025
is an excellent Bicep-based reference and starting point that helps you get up and running quickly [3].
Table 1
BICEP Resource Definitions
Resources Versioned w/@yyyy-mm-dd-state
Common
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07.10.2014
can run a ZooKeeper server in standalone mode or with replication; you can see a sample configuration in the online manual [2] [3]. The second case seems more favorable for distributed filesystems
18%
09.10.2017
if page.get('Contents') is not None:
21 for file in page.get('Contents'):
22 s3pump(file.get('Key'), bucket)
Data Highway?
For large S3 buckets with data in the multiterabyte ... 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
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28.11.2021
.14, although you can still resort to Docker Machine [3] in this case, which creates a virtual Linux system on the local host that you can then use to access the Docker engine. The example in Figure 1 uses
18%
21.03.2017
# ===================
09 #
10 if __name__ == '__main__':
11
12 f = h5py.File("mytestfile.hdf5", "w")
13
14 dset = f.create_dataset("mydataset", (100,), dtype='i')
15
16 dset[...] = np.arange(100)
17
