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81%
Parallel Programming with OpenCL
04.11.2011
Home »  HPC  »  Articles  » 
         // Add weighted value to convolution sum 13         convolutionSum += in.data[(y + ky) * in.width + (x + kx)] * kernel.data[ky * kernel.width + kx]; 14       } 15     } 16     // Clamp values to {0 ... We take a close look at how to integrate graphics processors into your parallel programs with OpenCL.
81%
Preload Trick
11.05.2021
Home »  HPC  »  Articles  » 
was: # This is the configuration file to use NVBLAS Library NVBLAS_LOGFILE  nvblas.log NVBLAS_CPU_BLAS_LIB  /usr/lib/x86_64-linux-gnu/libopenblas.so.0 NVBLAS_GPU_LIST 0 NVBLAS
81%
Data Analysis with R and Python
17.02.2015
Home »  Archive  »  2015  »  Issue 25: Safe...  » 
Lead Image © mopic, 123RF.com
= ro.r.table(ro.r.cut(rep.df.rx2(1), [0, 0.9999, 1.0001, 2])) 14 15 label = lambda label, i: "%s %s %%" %(label, round((vals[i]*100)/num)) 16 labels = [label("Ellipse", 0), label("Parabola", 1), label
81%
Programming with OpenMP
07.11.2011
Home »  HPC  »  Articles  » 
, how can you get all the threads to work on a collated result – for example, to total the values in an array? reduction() (Listing 2) handles this. Listing 2: reduction() 01 a = 0 ; b = 0 ; 02 #pragma
81%
Getting the most from your cores
11.10.2016
Home »  Archive  »  2016  »  Issue 35: Persi...  » 
Lead Image © ktsdesign, 123RF.com
_percent_local=psutil.cpu_percent(interval=interv,percpu=True); 52 cpu_percent.append(cpu_percent_local); 53 # end for 54 55 # Normalize epoch to beginning 56 epoch_list[:] = [x - epoch_list[0] for x in epoch_list]; 57 58 # Plots 59 60 ... CPU utilization metrics tell you how well your applications are using your processing resources.
81%
Security first with the Hiawatha web server
11.04.2016
Home »  Archive  »  2016  »  Issue 32: Measu...  » 
Lead Image © Tatiana Popov, 123RF.com
.1 #drop attempts to fool webserver to be insecure. You might want 1.0 #anti dos BanOnFlooding = 10/1:15 KickOnBan = yes # close all connections for an IP that is banned #MaxUrlLength = 500
80%
Thrashing the data cache for fun and profit
05.12.2019
Home »  Archive  »  2019  »  Issue 54: NVMe...  » 
Lead Image © Lucy Baldwin, 123RF.com
, producing a 16-fold increase in data cache misses, up from 6 million to 100 million events. Note how the row-major approach delivered a near-perfect result, with D1 cache misses coming in under one percent
80%
Profiling Python Code
09.12.2019
Home »  HPC  »  Articles  » 
 accelerations.    146       200         95.0      0.5      0.0      for i in range(0, d_num):    147     75150      29236.0      0.4      8.0          for j in range(0, p_num):    148     75000      57404.0      0.8     15
80%
Profiling Python code
30.01.2020
Home »  Archive  »  2020  »  Issue 55: AWS L...  » 
Lead Image ©-Yong Hian Lim, Fotolia.com
0.4 8.0 for j in range(0, p_num): 148 75000 57404.0 0.8 15.7 acc[i,j] = force[i,j]*rmass 149 # end
80%
From debugging to exploiting
17.02.2015
Home »  Archive  »  2015  »  Issue 25: Safe...  » 
Lead Image © Maksim Kabou, 123RF.com
can refer to the entire process environment by means of the **environ variable; therefore: (gdb) p &environ $4 = ( *) 0xf7f83d64 (gdb) x/100s *environ 0xffffc815

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