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Institut für Elektrische Energietechnik
Logo Institut für Elektrische Energietechnik
Institut für Elektrische Energietechnik
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IEET > Personal > Wissenschaftliche Mitarbeitende > Florian Strobel, M.Sc.

Florian Strobel

M.Sc.
Wissenschaftlicher Mitarbeiter

Kontakt

Florian Thorsten Lutz Strobel
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Harburger Schloßstraße 22a,
21079 Hamburg
Gebäude Harburger Schloßstraße 22a, Raum 2.014
Tel: +49 40 42878 2750
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Forschungsprojekt

DISEGO
Kritische Komponenten für den verteilten und sicheren Netzbetrieb

DISEGO

Kritische Komponenten für den verteilten und sicheren Netzbetrieb

Bundesministerium für Wirtschaft und Klimaschutz (BMWK); Laufzeit: 2022 bis 2025

zur Projektseite

Publikationen

TUHH Open Research (TORE)

2023

Lehrveranstaltungen

Stud.IP
link to course in Stud.IP Studip_icon
GPU Architectures and Programming
Semester:
SoSe 24
Course type:
Lecture
Course number:
lv3039_s24
Lecturer:
Prof. Dr. Sohan Lal
Description:
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
Pre-requisites:
- Basic course on computer architecture and C/C++ programming
Learning organisation:
- Weekly lecture - Weekly lab
Performance accreditation:
Oral exam + Lab assignments
Area classification:
Studiendekanat Elektrotechnik, Informatik und Mathematik
ECTS credit points:
6
Stud.IP informationen about this course:
Home institute: Institut für Massively Parallel Systems (E-EXK5)
Registered participants in Stud.IP: 81
Postings: 2
Documents: 1

Betreute Abschlussarbeiten

laufende
beendete
TU Hamburg
Institut für Elektrische Energietechnik (ieet) E-6
Prof. Dr.-Ing. Christian Becker
Harburger Schloßstraße 36
21079 Hamburg
E-Mail : ieet(at)tuhh.de
Tel : +49 40 42878 3213
Fax : +49 40 42878 2382
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