Hello 👋

I'm Abdullah Amawi

Graduate Research Assistant at Georg-August-Universität Göttingen
My focus is AI and Machine Learning at Georg-August-Universität Göttingen. My thesis, "Optimizing I/O Performance of Scalable ML Workflows in HPC Systems", provided foundational exposure to high-performance computing, Linux, and performance tuning. I possess strong technical skills and a keen interest in PC hardware, emerging technologies, and applied data science.
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My last projects </>

TensorRigs.com

TensorRigs.com
AI Hardware, ML GPUs, Deep Learning, PyTorch, TensorFlow

AI Hardware & ML GPUs resource for Deep Learning, PyTorch, TensorFlow & Neural Networks. Expert guides for machine learning GPUs (NVIDIA RTX, A100, H100), deep learning systems, and AI workstations. Compare hardware for PyTorch, TensorFlow, JAX, computer vision, NLP, and data science workloads.
TensorDocs - HPC & ML Documentation

TensorDocs - HPC & ML Documentation
Documentation, Starlight, HPC, Deep Learning

Comprehensive documentation website built with Starlight (Astro) covering high-performance computing, deep learning workflows, and ML optimization techniques. Includes guides on NVIDIA DALI, GPU acceleration, and scalable training pipelines.
GamerRigs.com

GamerRigs.com
Gaming Hardware, GPUs, Gaming Systems, 4K, VR

Gaming Hardware & High-Performance GPUs resource for 4K, 8K, VR & Streaming. Expert guides for gaming GPUs (NVIDIA RTX, AMD Radeon), gaming systems, and streaming rigs. Compare hardware for 4K, 8K, VR gaming, content creation, and streaming workloads.
Optimizing I/O Performance of Scalable ML Workflows in HPC Systems

Optimizing I/O Performance of Scalable ML Workflows in HPC Systems
Master Thesis, HPC, ML, DALI, PyTorch, TF

This thesis investigates data-loading bottlenecks in large-scale deep learning workflows. By integrating GPU-accelerated pipelines such as NVIDIA DALI, experiments show significant reductions in training time and improved GPU utilization, demonstrating the potential of efficient data pipelines to optimize HPC-based machine learning.
Starlight Documentation for Large-Scale Machine Learning in HPC

Starlight Documentation for Large-Scale Machine Learning in HPC
Documentation, HPC, Deep Learning

My collection of additional documentation that was the result of few software environment issues and challenges during my thesis work. Please note this is not the thesis documentation itself, but a small addition to document how to address some of the issues that may face you in HPC and deep learning workloads, and some additional info. This work can be helpful to anyone that has a similar project or workload.
Sentiment Analysis on Course Feedback

Sentiment Analysis on Course Feedback
Sentiment Analysis, NLP, Python, ML

This project explores the use of natural language processing (NLP) for sentiment analysis. It provides an overview of NLP concepts, recent advancements in sentiment analysis, and demonstrates its application on student feedback collected from a teaching seminar. Key scientific papers in the field are also reviewed to contextualize the analysis.
Göttingen University Research Group Lab Website

Göttingen University Research Group Lab Website
Research, AI, Web Development

Research group Lab website. The lab is a dedicated research and development environment designed to support cutting-edge work in three key fields: Swarm Intelligence, Wireless Sensor Networks, and Artificial Intelligence. Established to empower our students and researchers, the lab provides the infrastructure necessary for seminars, practical sessions, projects, and thesis work.
ZombieSim

ZombieSim
HPC, Parallel Computing, C++, OpenMP, MPI

This Project presents ZombieSim, a parallelized simulation designed to explore High-Performance Computing (HPC) concepts. By combining a configurable program with a game engine for visualization, the project demonstrates practical parallelization techniques and performance analysis, providing insights into efficient HPC utilization.