30%
19.10.2012
is US$ 3.1/hour.
Thus, using the small usage case (80 cores, 4GB of RAM per core, and basic storage of 500GB) would cost US$ 24.00/hour (10 Eight Extra Large Instances). The larger usage case (256 cores
30%
03.01.2013
-1.el6 epel 9.1 M
Installing for dependencies:
GraphicsMagick x86_64 1.3.17-1.el6 epel 2.2 M
GraphicsMagick-c++ x86_64 1.3.17-1.el6
30%
23.07.2013
admin (Table 1).
Table 1: PowerDNS Features
Authoritative DNS server (hosting)
Resolving DNS server (caching)
API to provision zones and records
DNSSEC support (as of 3.x
30%
04.11.2011
:
[http://forums.amd.com/devforum/messageview.cfm?catid=390&threadid=125792]
[8] CUDA toolkit download:
[http://developer.nvidia.com/object/cuda_3_2_downloads.html#Linux]
[9] NVidia pre
30%
25.08.2016
seen much more interest in Nano (Figure 3), partly, I believe, because Nano has the command help at the bottom of the screen at all times, which, if you don't use Nano very often, can be very, well
30%
08.07.2018
a range of hosts on the command line:
$ pdsh -w host[1-11] uname -r
$ pdsh -w host[1-4,8-11] uname -r
In the first case, pdsh
expands the host range to host1
, host2
, host3
, etc., through host11
30%
19.09.2019
add_ufunc(x, y):
return x + y
The decorator line defines the data types (i.e., int64
here) and the target for the decorator cuda
. A simple test for the add_ufunc
Numba function is:
a = np.array([1, 2, 3, 4])
b ... High-Performance Python 3
30%
07.03.2019
that lend themselves to parallelizing with directives. You can parallelize each loop individually (Table 2), giving you more control, or you can combine loop directives into a single directive (Table 3
30%
19.11.2019
, ioengine=libaio, iodepth=32
fio-3.12
Starting 1 process
Jobs: 1 (f=1): [w(1)][100.0%][w=475MiB/s][w=122k IOPS][eta 00m:00s]
test: (groupid=0, jobs=1): err= 0: pid=1634: Mon Oct 14 22:18:59 2019
write: IOPS=118k, BW=463Mi
30%
18.03.2020
2 hours ago 9.83GB
49cbd14ae32f 3 hours ago 269MB
ubuntu 18.04 72300a873c2c 3 weeks ago 64.2MB
