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IEET > Staff > Research Assistants > Marwan Mostafa, M.Sc.

Marwan Mostafa

M.Sc.
Research Assistant

Contact

Marwan Mostafa, M.Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Office Hours
nach Vereinbarung/ by appointment
Harburger Schloßstraße 36,
21079 Hamburg
Building HS36, Room C3 0.013
Phone: +49 40 42878 4097
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Research Project

iNeP
Integrated network planning for the electricity, gas and heat sectors

iNeP

Integrated network planning for the electricity, gas and heat sectors

Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2021 to 2026

to the project page

Publications

TUHH Open Research (TORE)

2023

2022

2021

Courses

Stud.IP
zur Veranstaltung in Stud.IP Studip_icon
GPU Architecture
Semester:
SoSe 23
Veranstaltungstyp:
Vorlesung (Lehre)
DozentIn:
Prof. Dr. Sohan Lal
Beschreibung:
In this module, you will study the architecture and programming of GPUs. Please find below a brief outline of the lectures: - Review of computer architecture basics - measuring performance, benchmarks, five-stage RISC pipeline, caches - GPU basics - the evolution of GPU computing, a high-level overview of a GPU architecture - GPU programming with CUDA - program structure, CUDA threads organization, warp/thread-block scheduling - GPU (micro) architecture - streaming multiprocessors, single instruction multiple threads (SIMT) core design, tensor cores for deep learning, RT cores for ray tracing, mixed-precision support - GPU memory hierarchy - banked register file and operand collectors, shared memory, GPU caches (differences w.r.t. CPU caches), global memory - Branch and memory divergence - branch handling, stack-based reconvergence, memory coalescing, coalescer design - Barriers and synchronization - Temporal and spatial locality exploitation challenges in GPU caches - Global memory- high throughput requirements, GDDR/HBM, memory bandwidth optimization techniques - GPU research issues - performance bottlenecks, GPU power modeling, high-power consumption/energy efficiency, GPU security - Application case study - deep learning - Cycle-accurate simulators for GPUs In addition to lectures, a semester-long problem-based project will augment the learning in the lectures. Several topics related to GPUs will be proposed. You are required to choose a topic and work on it. It is possible to work in groups. There will be (bi-) weekly meetings to discuss progress and problems. In addition to the semester-long project, there will be assignments to teach CUDA programming. Course Evaluation: Oral examination Duration: 30 minutes
Voraussetzungen:
An introductory module on basic computer architecture or a similar module, and good programming skills in C/C++.
Leistungsnachweis:
Project/assignments + 30-minute oral exam
Bereichseinordnung:
Studiendekanat Elektrotechnik, Informatik und Mathematik
ECTS-Kreditpunkte:
6
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Massively Parallel Systems (E-EXK5)
In Stud.IP angemeldete Teilnehmer: 37
Anzahl der Dokumente im Stud.IP-Downloadbereich: 15

Supervised Theses

ongoing
completed

2022

  • Barthelme, J. (2022). Technisch-ökonomische Systemmodellierung und -anlayse eines urbanen Quatiers hinsichtlich des Einsatz von Wasserstoff als primärer Energieträger.

TU Hamburg
Institute of Electrical Power and Energy Technology (ieet) E-6
Prof. Dr.-Ing. Christian Becker
Harburger Schloßstraße 36
21079 Hamburg
E-mail : ieet(at)tuhh.de
Phone : +49 40 42878 3213
Fax : +49 40 42878 2382
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