iNeP - integrierte Netzentwicklungsplanung für die Energieträger Strom, Gas und Wärme Vorwerk, Daniela; Schulz, Detlef; Micheely, Stefan; Koch, Oliver Henry; Cosler, Cristoph; Heise, Johannes; Mostafa, Marwan; Povel, Alexander; Töbermann, Christian Stand der Technik und Digitalisierung bei integrierten Energiesystemen, Sektorenkopplungs- und Mobilitätstechnologien. - Hamburg : HSU, 2021. - (Hamburger Beiträge zum technischen Klimaschutz ; Bd. 3). - Seite 47-56 (2021)
Open Access
|
Verlags DOI
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
Barthelme, J. (2022). Technisch-ökonomische Systemmodellierung und -anlayse eines urbanen Quatiers hinsichtlich des Einsatz von Wasserstoff als primärer Energieträger.