Add Hristiyan`s final presentation and blog post

.github/actions/spelling/allow/terms.txt

@@ -134,6 +134,7 @@ GSCHEP
 GSMODE
 HOMMEXX
 IDD
+interactable
 interoperate
 IPDPS
 jacobians
@@ -202,6 +203,7 @@ Fibroblasts
 fibroblasts
 Hesam
 macrophages
+Mandelbrot
 MDSCs
 Montigny
 Mutlu
@@ -219,3 +221,4 @@ LibTorch
 Nanjing
 pytorch
 PyTorch
+unoptimised

_data/standing_meetings.yml

@@ -3,6 +3,10 @@
   time_cest: "17:00"
   connect: "[Link to zoom](https://princeton.zoom.us/j/97915651167?pwd=MXJ1T2lhc3Z5QWlYbUFnMTZYQlNRdz09)"
   agenda:
+    - title: "Creating teaching materials with xeus-cpp final report"
+      date: 2026-06-10 17:00:00 +0200
+      speaker: "Hristiyan Shterev"
+      link: "[Slides](/assets/presentations/Hristiyan-Shterev-Teaching-materials-with-xeus-cpp-final.pdf)"
     - title: "Enhance Clang Diagnostics Initial Presentation"
       date: 2026-05-27 17:00:00 +0200
       speaker: "Aditya Medhane"

_posts/2026-06-10-creating-teaching-materials-xeus-cpp-final.md

@@ -0,0 +1,68 @@
+---
+title: "Final report for creating teaching materials with xeus-cpp"
+layout: post
+excerpt: "A Final report of my project about creating notebooks for CUDA and OpenMP with xeus-cpp"
+sitemap: false
+author: Hristiyan Shterev
+permalink: /blogs/xeus-cpp_Hristiyan_Shterev_blog_final/
+thumbnail_image: /images/mg-pld-logo.png
+date: 2026-06-10
+tags: c++ xeus-cpp jupyter internship systems-programming high-school cuda
+---
+
+
+{% include dual-banner.html
+left_logo="/images/mg-pld-logo.png"
+right_logo="/images/cr-logo_old.png"
+caption=""
+height="20vh" %}
+
+## Main goals of this project
+
+The main goal of this project was to create interactable examples for the for the CUDA and OpenMP programming models, targeting beginners who want hands-on experience with parallel computing on both the GPU and CPU. 
+
+Each notebook builds on the previous one, introducing new concepts gradually through working code examples.
+
+Together the 16 notebooks cover the full beginner to intermediate journey - from launching a first thread to understanding memory hierarchies, synchronisation primitives, and performance optimization on both CPU and GPU.
+
+## The CUDA notebooks
+
+The CUDA notebooks include 8 different examples that add to one another. Here is what each one explains:
+
+- The first notebook is a basic introduction to CUDA with simple examples like the __global__ kernel usage and calling it.
+- Next we introduce some more fundamental concepts.
+- The third notebook shows how using parallel programming can speed up if we use the threads the right way.
+- After that we show thread cooperation. The threads split the work instead of having one thread per task
+- Then we demonstrate The Julia set. A complex mathematical shape.
+- The sixth example creates a ripple pattern.
+- Next we demonstrate the dot product. A mathematical operation that takes two equal-length vectors and returns a single regular number
+- Lastly there is a simple ray tracing example.
+
+### CUDA benchmark vs the CPU
+
+This benchmark adds two vectors with 10 million elements each into a third one. This is done 3 times using different methods.
+
+- The first one is a basic CPU only demonstration. The time is around 21 ms.
+- The second example is using the GPU but with only 1 thread per block. We can see that this is slower compared to the first one. This is a very unoptimized way to use the device.
+- The third method is now a lot faster than the other 2. We make each block use 256 threads which speeds up the time by a lot - around 2 milliseconds.
+
+<img src="/images/blog/cuda-vs-cpu-benchmark.png" alt="Benchmarked comparison of CUDA vs the CPU" style="max-width: 70%; height: auto; display: block; margin: 0 auto;">
+
+## The OpenMP notebooks
+
+The OpenMP notebooks also include 8 different examples that add to one another. Here is what each one explains:
+
+- The first notebook is a basic introduction to OpenMP with simple examples like the #pragma omp parallel directive and thread creation. 
+- Next we introduce the fork-join model and how threads are spawned and joined back together.
+- Then we demonstrate the Pi integral. A mathematical problem solved by splitting the work across multiple threads. 
+- The fourth notebook calculates the area of the Mandelbrot set. A complex mathematical shape rendered in parallel by assigning different regions to different threads.
+- After that we show linked list traversal. How pointer-based data structures interact with parallel execution. 
+- The sixth example demonstrates race conditions. What happens when threads write to the same memory without protection and how to fix it.
+- Next we demonstrate false sharing. How threads can slow each other down even when touching different variables due to CPU cache line behaviour. 
+- Lastly there is Conway's Game of Life. A grid simulation where threads compute the next generation in parallel using double buffering to avoid race conditions by design.
+
+## Related links
+
+- [Xeus-cpp repository](https://github.com/compiler-research/xeus-cpp)
+- [My github account](https://github.com/HrisShterev)
+- [Notebooks repository](https://github.com/compiler-research/live-cpp-tutorials/)