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All Intro to GPUs content
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‎_toc.yml

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- file: individual_modules/intermediate_version_control/rewriting_history
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- file: individual_modules/intermediate_version_control/further_topics
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- file: individual_modules/intermediate_version_control/resources
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- file: course_homepages/GPUs
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sections:
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- file: individual_modules/section_landing_pages/introduction_to_GPUs
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sections:
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- file: individual_modules/intro_to_GPUs/theory
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- file: individual_modules/intro_to_GPUs/spack
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- file: individual_modules/intro_to_GPUs/slurm
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- file: individual_modules/intro_to_GPUs/conways_game_of_life
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- file: individual_modules/intro_to_GPUs/profiling
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- file: individual_modules/intro_to_GPUs/temperature_diffusion
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- file: individual_modules/bibliography
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- caption: Short Courses
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chapters:

‎course_homepages/GPUs.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "4cd0d89f-b3b7-4360-8ae3-f47c15958c8e",
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"metadata": {},
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"source": [
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"# GPUs\n",
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"\n",
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"The following set of courses discuss GPUs. The details for each of the courses can be found on their respective pages. \n",
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"\n",
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"## Introduction to GPUS Self Study Notes\n",
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"\n",
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"[Clickable Link to Self Study Notes](../individual_modules/section_landing_pages/introduction_to_GPUs.md)\n",
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"\n",
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"This course provides all the essential tools to leverage GPUs effectively, guiding participants through GPU programming, software management, and performance optimisation while offering direct comparisons with CPU implementations. Through hands-on examples such as Conway’s Game of Life and temperature diffusion, learners explore practical high-performance computing techniques, including profiling, Slurm job scheduling, and Spack-based environment setup. The material bridges theory and practice, equipping participants to translate computational concepts into efficient, scalable workflows on modern HPC systems."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_A100-SXM4-80GB_AMD_EPYC_7V12_64-Core_Processor_cpu_gpu_naive_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_A100-SXM4-80GB_AMD_EPYC_7V12_64-Core_Processor_cpu_gpu_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_A100-SXM4-80GB_AMD_EPYC_7V12_64-Core_Processor_gpu_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_GeForce_RTX_3070_AMD_Ryzen_9_5950X_16-Core_Processor_cpu_gpu_naive_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_GeForce_RTX_3070_AMD_Ryzen_9_5950X_16-Core_Processor_cpu_gpu_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_GeForce_RTX_3070_AMD_Ryzen_9_5950X_16-Core_Processor_gpu_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_H100_NVL_AMD_EPYC_9V84_96-Core_Processor_cpu_gpu_naive_ts100.csv

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‎individual_modules/intro_to_GPUs/_static/game_of_life_data/gol_timings_NVIDIA_H100_NVL_AMD_EPYC_9V84_96-Core_Processor_cpu_gpu_ts100.csv

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NVIDIA_H100_NVL,AMD_EPYC_9V84_96-Core_Processor,CuPy (GPU),2500,100,2.688642,0.313695
14+
NVIDIA_H100_NVL,AMD_EPYC_9V84_96-Core_Processor,NumPy (CPU),5000,100,57.519849,0.447362
15+
NVIDIA_H100_NVL,AMD_EPYC_9V84_96-Core_Processor,CuPy (GPU),5000,100,2.872334,0.298268
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NVIDIA_H100_NVL,AMD_EPYC_9V84_96-Core_Processor,NumPy (CPU),10000,100,222.391967,1.363038
17+
NVIDIA_H100_NVL,AMD_EPYC_9V84_96-Core_Processor,CuPy (GPU),10000,100,3.946568,0.353731

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