Lehrveranstaltungen in Stud.IP

aktuelles Semester
zur Veranstaltung in Stud.IP Studip_icon
GPU Architectures and Programming
Semester:
SoSe 24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv3039_s24
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:
- Basic course on computer architecture and C/C++ programming
Lernorganisation:
- Weekly lecture - Weekly lab
Leistungsnachweis:
Oral exam + Lab assignments
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: 82
Anzahl der Postings im Stud.IP-Forum: 2
Anzahl der Dokumente im Stud.IP-Downloadbereich: 1
voriges Semester
zur Veranstaltung in Stud.IP Studip_icon
GPU Architectures and Programming
Semester:
SoSe 24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv3039_s24
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:
- Basic course on computer architecture and C/C++ programming
Lernorganisation:
- Weekly lecture - Weekly lab
Leistungsnachweis:
Oral exam + Lab assignments
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: 82
Anzahl der Postings im Stud.IP-Forum: 2
Anzahl der Dokumente im Stud.IP-Downloadbereich: 1

Lehrveranstaltungen

Informationen zu den Lehrveranstaltungen und Modulen entnehmen Sie bitte dem aktuellen Vorlesungsverzeichnis und dem Modulhandbuch Ihres Studienganges.

Modul / Lehrveranstaltung Zeitraum ECTS Leistungspunkte
Modul: Elektrische Energiesysteme I: Einführung in elektrische Energiesysteme WiSe 6
Modul: Elektrische Energiesysteme II: Betrieb und Informationssysteme elektrischer Energienetze WiSe 6
Modul: Elektrische Energiesysteme III: Dynamik und Stabilität elektrischer Energiesysteme SoSe 6
Modul: Elektrotechnik II: Wechselstromnetzwerke und grundlegende Bauelemente SoSe 6
Modul: Elektrotechnisches Projektpraktikum SoSe 6
Modul: Prozessmesstechnik SoSe 4
Modul: Smart-Grid-Technologien WiSe, SoSe 6

Lehrveranstaltung: Seminar zu Elektromagnetischer Verträglichkeit und Elektrischer Energiesystemtechnik

weitere Information

WiSe, SoSe 2

SoSe: Sommersemester
WiSe: Wintersemester