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27%
Embarrassingly parallel computation
01.06.2024
Home »  Archive  »  2024  »  Issue 81: Load...  » 
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
27%
Goodbye virtual machines, hello microVMs
06.10.2022
Home »  Archive  »  2022  »  Issue 71: Kuber...  » 
Photo by Eric Froehling on Unsplash
([hostPort:]containerPort) ubuntu1804 1 weaveworks/ignite-ubuntu:18.04 weaveworks/ignite-kernel:5.13.3 2 2G 20G 22,38080,52812,58080 centos8 1 weaveworks/ignite-centos:8 weaveworks/ignite-kernel:5.13.3 2 2G
27%
Protecting your web application infrastructure with the Nginx Naxsi firewall
18.07.2013
Home »  Archive  »  2013  »  Issue 15: What’...  » 
Pansiri Pikunkaew, 123RF
proxy_intercept_errors on; 17 ... 18 Filming location 19 ... 20 error_page 502 @ fallback; 21 proxy_next_upstream HTTP_500 http_502 http_503 http_504 timeout error invalid_header; 22 proxy_pass http
27%
Data Compression as a CPU Benchmark
28.11.2021
Home »  Archive  »  2021  »  Issue 66: Inci...  » 
Lead Image © Lucy Baldwin, 123RF.com
Compiler: Apple LLVM 12.0.5 (clang-1205.0.22.9) GCC 4.2.1 CLANG 12.0 Darwin : 20.4.0 : Darwin Kernel Version 20.4.0: PageSize:16KB Apple M1 8C8T RAM size: 16384 MB, # CPU hardware threads: 8 RAM usage
26%
High-Performance Python 3
19.09.2019
Home »  HPC  »  Articles  » 
 sklearn.model_selection import train_test_split from sklearn.metrics import mean_squared_error   from cuml.linear_model import LinearRegression as cuLR     n_samples = 2**20 n_features = 399   # Generate Data X,y = make_regression(n_samples=n
26%
When I/O workloads don't perform
02.08.2021
Home »  Archive  »  2021  »  Issue 64: Bare...  » 
Lead Image © Viacheslav Iakobchuk, 123RF.com
%util sda 10.91 6.97 768.20 584.64 4.87 18.20 30.85 72.31 13.16 20.40 0.26 70.44 83.89 1.97 3.52 nvme0n1 58.80 12.22 17720.47 48.71 230
26%
Matlab-like tools for high-performance computing
16.05.2013
Home »  Archive  »  2013  »  Issue 14: Samba 4  » 
x86_64 6:3.4.3-1.el6 epel 9.1 M Installing for dependencies: GraphicsMagick x86_64 1.3.17-1.el6 epel 2.2 M GraphicsMagick-c++ x
26%
When I/O Workloads Don’t Perform
12.05.2021
Home »  HPC  »  Articles  » 
  30.85  72.31   13.16   20.40   0.26    70.44    83.89   1.97   3.52 nvme0n1         58.80   12.22  17720.47     48.71   230.91     0.01  79.70   0.08    0.42    0.03   0
26%
mpi4py – high-performance distributed Python
30.11.2020
Home »  Archive  »  2020  »  Issue 60: Secur...  » 
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
26%
Data Analysis with R and Python
17.02.2015
Home »  Archive  »  2015  »  Issue 25: Safe...  » 
Lead Image © mopic, 123RF.com
for x in rep.df.rx2(2)]) 17 18 devs.png(file=path, width=512, height=512) 19 ro.r.plot(x_vals, y_vals, xlab=x_lab, ylab=y_lab, main=main) 20 devs.dev_off() 21 22 rep ... The statistical programming language R dissects its database in a masterful way, and you can embed your R in Python using the Rpy2 interface.

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