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18%
Small-board computers
17.02.2015
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Lead Image © Author, 123RF.com
: Tegra X1: 25.6GBps memory bandwidth HDMI 2.0 and HDCP 2.2 10W power Peak performance: 1,024GFLOPS with FP16; 512GFLOPS with FP32 ARM Cortex CPUs: Quad-core 64-bit ARM Cortex-A57 ... 25
18%
Modularize websites with Web Components
09.04.2019
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Lead Image © Andrey Prokhorov, fotolia.com
; 15 border:1px solid #aaa; 16 } 17 18 article { 19 margin: auto; 20 float:left; 21 margin-left: 20%; 22 margin-right: 30%; 23 } 24 25 li { 26 --anot-item-bg: #ff6699; 27 } The inner
17%
When I/O workloads don't perform
02.08.2021
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Lead Image © Viacheslav Iakobchuk, 123RF.com
- 28 (Min/Max 22/28) 191 G-Sense_Error_Rate 0x0032 100 100 --- Old_age Always - 0 192 Power-Off_Retract_Count 0x0032 100 100 --- Old_age Always - 35 193
17%
Embarrassingly parallel computation
01.06.2024
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Lead Image © Lucy Baldwin, 123RF.com
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
17%
When I/O Workloads Don’t Perform
12.05.2021
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_age   Always       -       28 (Min/Max 22/28) 191 G-Sense_Error_Rate      0x0032   100   100   ---    Old_age   Always       -       0 192 Power-Off_Retract_Count 0x0032   100   100   ---    Old_age   Always       -       35 193
17%
Tuning I/O Patterns in Fortran 90
04.12.2013
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if (ierr > 0) then 21 write(*,*) "error in opening file! Stopping" 22 stop 23 else 24 do 10 counter=1,counter_limit 25 my_record%x = counter 26 my_record%y = counter
17%
Matlab-like tools for high-performance computing
16.05.2013
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://wiki.scilab.org/Linalg%20performances Compiling http://wiki.scilab.org/Compiling%20Scilab%205.x%20under%20GNU-Linux%20Unix Parallel computing http
17%
Getting started with the OpenStack cloud computing framework
28.06.2011
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) layer for the cloud, virtualizing the various hardware components and making them available through a standard API. The first OpenStack release (dubbed "Austin") became available October 22 [3]; The Open
17%
mpi4py – high-performance distributed Python
30.11.2020
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Lead Image © liu liming, 123RF.com
): 11 12 s = 0.0 13 s += h * f(a) 14 for i in range(1, n): 15 s += 2.0 * h * f(a + i*h) 16 # end for 17 s += h * f(b) 18 return (s/2.) 19 # end def 20 21 22 # Main section 23 comm = MPI
17%
Configuration management with Chef
30.11.2025
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© Alistair Cotton, 123RF.com
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

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