I'm starting a new project and would like to parallelize some computations. I've used OpenMP in the past, but am aware that now many STL algorithms can be paral
I'm running a simple kernel which adds two streams of double-precision complex-values. I've parallelized it using OpenMP with custom scheduling: the slice_indic
I'm testing the memory bandwidth on a desktop and a server. Sklyake desktop 4 cores/8 hardware threads Skylake server Xeon 8168 dual socket 48 cores (24 per so
Normally I compile code (all in a single file main.c) with the intel oneapi command prompt like so icl.exe main.c -o binary_name I can then run binary_name.exe
I have N number of text files. I am trying to read from those files parallelly, so I have forked N threads and each thread gets one text file from those N files
Here is my Matrix Multiplication C++ OpenMP code that I have written. I am trying to use OpenMP to optimize the program. The sequential code speed was 7 seconds
I'm attempting to benchmark the memory bandwidth on a ccNUMA system with 2x Intel(R) Xeon(R) Platinum 8168: 24 cores @ 2.70 GHz, L1 cache 32 kB, L2 cache 1 MB a
For a small benchmark of OpenMP on an i7-6700K I wrote the following code: #include <iostream> #include <omp.h> #include <vector> #include <
I'm new in C and have some problems compiling my code in OS X. I code Java a lot both in Eclipse and use terminal to compile my code. However now I'm learning
I'm trying to set up an OpenMP project using Clang (3.7.0) on my laptop running Linux Mint. Now I've read that OpenMP is not supported right away so I followed