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04.12.2024
capable of read speeds up to 4,900MBps (and up to 3,700MBps write speed), with total capacity of 512GB [6] (about $70). The unit is rated at a staggering 400K read and 900K write I/O operations per second
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02.02.2021
:
In Equation 1, a
is the application speedup, n
is the number of processors, and p
is the "parallel fraction" of the application (i.e., the fraction of the application that is parallelizable), ranging from 0
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18.02.2018
supports various encryption and decryption methods, for automatic data decoding. In the Clevis world, these methods are known as PINs (hence the name Clevis and Tang) [6]. The Tang service can be used
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05.12.2019
to send STDOUT to a file or you can use the notation
$this_value = `this_program 1>&2`;
to catch a program's STDOUT and STDERR. This example shows the backtick method, but you can also use the open
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04.10.2018
of their internal 2.5-inch SATA devices, coming in at a mere 2.3x3x0.5 inches (5.8x7.6x1.3 cm) – smaller than a Post-it note (Figure 1). Available in sizes ranging from 256GB to 2TB, the specimen in our lab is the MU
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03.04.2019
in Table 3 that you can nest parallel regions. The first parallel region will use N
threads (N
cores), and the second parallel region (the nested parallel region) will use N
threads for each thread
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26.01.2025
in combination with a card supporting the extended standard (SDXC). CQ mode was introduced in 2017 with version 6.0 of the SD specification [4], but although the Linux kernel had been supporting CQ mode for e
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01.02.2013
at the output of uptime
[1] on OS X:
13:03 up 2 days, 12:01, 2 users, load averages: 0.52 0.59 0.63
The uptime
command displays the load average in its common form, averaging the last one, five, and 15
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19.10.2012
12-core AMD processors ranging in speed from 2.2 to 2.9GHz with 24 to 128GB of RAM per server and up to 1TB of scratch local storage per node.
Getting applications running POD HPC clouds can be quite
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12.03.2014
important data structure in NumPy is the N
-dimensional array, ndarray
. In a one-dimensional case, ndarrays
are vectors. Unlike Python lists, the size of NumPy arrays is immutable; its elements
