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vgvassilev merged 4 commits into from
Mar 4, 2026
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Fixing notebook in Hristiyan`s blog #369

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ad8c995
Delete images/blog/MergeSortTest.png
HrisShterev Mar 2, 2026
698acba
Update 2026-03-01-Creating teaching materials for C++ and CUDA with x…
HrisShterev Mar 2, 2026
0f7d133
Fixed typos
HrisShterev Mar 2, 2026
4847030
Update terms.txt
HrisShterev Mar 2, 2026
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6 changes: 6 additions & 0 deletions .github/actions/spelling/allow/terms.txt
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Expand Up @@ -48,14 +48,17 @@ backpropagation
biodynamo
bioinformatics
blogs
chrono
cms
codegen
consteval
cout
cplusplus
cppyy
cytokine
cytokines
doxygen
endl
gitlab
gpu
gridlay
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llvm
meetinglist
microenvironments
nomarkdown
omp
openmp
oop
Expand All @@ -82,6 +86,7 @@ rntuple
samtools
samtoramntuple
sbo
setprecision
sitemap
softsusy
superbuilds
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meetup
metaprogramming
Miapb
milli
multilanguage
omnidisciplinary
optimisation
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142 changes: 136 additions & 6 deletions _posts/2026-03-01-Creating teaching materials for C++ and CUDA with xeus-cpp.md
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author: Hristiyan Shterev
permalink: blogs/xeus_cpp_Hristiyan_Shterev_blog/
date: 2026-03-01
tags: xeus-cpp cuda jupyter c++ xeus
tags: xeus-cpp cuda jupyter c++ xeus internship high-school systems-programming
custom_css: jupyter
---

{% include dual-banner.html
left_logo="/images/mg-pld-logo.png"

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right_logo="/images/cr-logo_old.png"
caption=""
height="20vh" %}
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## Example

**CPU - std::sort vs GPU - Merge sort speed test**

The example below shows a C++ benchmark comparing the performance of sorting a large array on a CPU versus a GPU. It provides a clear visual of how parallel processing can drastically outperform traditional sequential execution for data-heavy tasks.

<img src="/images/blog/MergeSortTest.png"/>
{::nomarkdown}

<div tabindex="-1" id="notebook" class="border-box-sizing">
<div class="container" id="notebook-container">
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt"></div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="CPU - std::sort vs GPU - Merge sort speed test">CPU - std::sort vs GPU - Merge sort speed test<a class="anchor-link" href="#CPU - std::sort vs GPU - Merge sort speed test">&#182;</a></h1>
<p>
The example below shows a C++ benchmark comparing the performance of sorting a large array on a CPU versus a GPU. It provides a clear visual of how parallel processing can drastically outperform traditional sequential execution for data-heavy tasks.
</p>

<p>
In the first cell we create the unsorted data that is going to be sorted by the CPU and GPU. We have loaded a compiled CUDA .so file beforehand.
</p>
</div>
</div>
</div>

<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[1]:</div>
<div class="inner_cell">
<div class="input_area">
<div class=" highlight hl-c++">
<pre>
<span class="kt">unsigned int</span> <span class="n">N_bench = <span class="mi">1048576</span>;</span>
<span class="n">std<span class="o">::</span>vector<</span><span class="kt">unsigned int</span><span class="n">> data_cpu(N_bench);</span>
<span class="n">std<span class="o">::</span>vector<</span><span class="kt">unsigned int</span><span class="n">> data_gpu(N_bench);</span>

<span class="k">for</span> <span class="p">(</span><span class=
"kt">unsigned int</span> <span class="n">i</span> <span class="o">=</span> <span class=
"mi">0</span><span class="n">;</span> <span class="n">i</span> <span class=
"o">&lt;</span> <span class="n">N_bench;</span></span> <span class="n">i</span><span class="o">++</span><span class=
"n">)</span> <span class="p">{</span>
<span class="kt">unsigned int </span><span class="n">val = N_bench - i;</span>
<span class="n">data_cpu[i] <span class="o">=</span> val;</span>
<span class="n">data_gpu[i] <span class="o">=</span> val;</span>
<span class="p">}</span>
</pre>
</div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt"></div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="CPU and GPU sorting">CPU and GPU sorting<a class="anchor-link" href="#CPU and GPU sorting">&#182;</a></h1>
<p>
Next we use std::sort and merge_sort_gpu_full function form the loaded CUDA code and measure the time the CPU and GPU sorts the data.
</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
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<div class=" highlight hl-c++">
<pre>
<span class="k">auto</span> <span class="n">start_cpu = std<span class="o">::</span>chrono<span class="o">::</span>high_resolution_clock<span class="o">::</span>now();</span>
<span class="n">std<span class="o">::</span>sort(data_cpu.begin(), data_cpu.end());</span>
<span class="k">auto</span> <span class="n">end_cpu = std<span class="o">::</span>chrono<span class="o">::</span>high_resolution_clock<span class="o">::</span>now();</span>

<span class="n">std<span class="o">::</span>chrono<span class="o">::</span>duration&lt;double, std<span class="o">::</span>milli&gt; cpu_ms <span class="o">=</span> end_cpu - start_cpu;</span>

<span class="k">auto</span> <span class="n">start_gpu = std::chrono::high_resolution_clock::now();</span>
<span class="n">merge_sort_gpu_full(data_gpu.data(), N_bench);</span>
<span class="k">auto</span> <span class="n">end_gpu = std::chrono::high_resolution_clock::now();</span>

<span class="n">std<span class="o">::</span>chrono<span class="o">::</span>duration&lt;double, std<span class="o">::</span>milli&gt; gpu_ms <span class="o">=</span> end_gpu - start_gpu;</span>
</pre>
</div>
</div>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered">
<div class="prompt input_prompt"></div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="">Printing the times and comparing them<a class="anchor-link" href="#Printing the times and comparing them">&#182;</a></h1>
<p>
Finally we print both times and compare them to see how much faster parallel processing is.
</p>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
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<div class=" highlight hl-c++">
<pre>
<span class="n"><span class="kt">double</span> speedup = cpu_ms.count() / gpu_ms.count();</span>

<span class="n">std<span class="o">::</span>cout << <span class="s">"CPU (std::sort) took: "</span> << std<span class="o">::</span>fixed << std<span class="o">::</span>setprecision(<span class="mi">4</span>) << cpu_ms.count() << <span class="s">" ms"</span> << std<span class="o">::</span>endl;</span>
<span class="n">std<span class="o">::</span>cout << <span class="s">"GPU (Merge Sort) took: "</span> << gpu_ms.count() << <span class="s">" ms"</span> << std<span class="o">::</span>endl;</span>

<span class="n">std<span class="o">::</span>cout << std<span class="o">::</span>endl;</span>

<span class="n">std<span class="o">::</span>cout << <span class="s">"GPU Speedup: "</span> << speedup << <span class="s">" times faster than CPU"</span> << std<span class="o">::</span>endl;</span>
</pre>
</div>
</div>
</div>
</div>
</div>
<div class="output_wrapper">
<div class="output">
<div class="output_area">
<div class="prompt output_prompt">Out[3]:</div>
<div class="output_text output_subarea output_execute_result">
<pre>
CPU (std<span class="o">::</span>sort) took: 145.3539 ms
GPU (Merge Sort) took: 9.6199 ms

GPU Speedup: 15.1097 times faster than CPU
</pre>
</div>
</div>
</div>
</div>
</div>
</div>

<br /> <br /> <br />

{:/}

## Related links

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