This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals. Also, students will walk through application of GPUs to sorting of data and processing images, implementing their own software using these techniques and libraries.
von
Spezialisierung GPU ProgrammingJohns Hopkins UniversityÜber diesen Kurs
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 3 von 4 in
Stufe „Mittel“
Some experience in C/C++ programming
Ca. 29 Stunden zum Abschließen
Englisch
Untertitel: Englisch
Was Sie lernen werden
Students will learn to develop software that can be run in computational environments that include multiple CPUs and GPUs.
Students will develop software that uses CUDA to create interactive GPU computational processing kernels for handling asynchronous data.
Students will use CUDA, hardware memory capabilities, and algorithms/libraries to solve programming challenges including image processing.
Kompetenzen, die Sie erwerben
- Cuda
- Algorithms
- C/C++
- GPU
- Nvidia
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Kurs 3 von 4 in
Stufe „Mittel“
Some experience in C/C++ programming
Ca. 29 Stunden zum Abschließen
Englisch
Untertitel: Englisch
von
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Lehrplan - Was Sie in diesem Kurs lernen werden
4 Stunden zum Abschließen
Course Overview
The purpose of this module is for students to understand how the course will be run, topics, how they will be assessed, and expectations.
4 Stunden zum Abschließen
3 Videos (Gesamt 11 min), 1 Lektüre, 1 Quiz
10 Stunden zum Abschließen
Multiple CPU/GPU Systems
In professional settings, use of one CPU managing one GPU, is not a viable configuration to solve complex challenges. Students will apply CUDA capabilities for allowing multiple CPUs to communicate and manage software kernels on multiple GPUs. This will allow for scaling the size of input data and computational complexity. Students will learn the advantages and limitations of this form of synchronous processing.
10 Stunden zum Abschließen
7 Videos (Gesamt 32 min)
4 Stunden zum Abschließen
CUDA Events and Streams
Students will learn to utilize CUDA events and streams in their programs, to allow for asynchronous data and control flows. This will allow more interactive and long-lasting software, including analytic user interfaces, near live-streaming video or financial feeds, and dynamic business processing systems.
4 Stunden zum Abschließen
5 Videos (Gesamt 28 min), 2 Lektüren, 1 Quiz
5 Stunden zum Abschließen
Sorting Using GPUs
The purpose of this module is for students to understand the basis in hardware and software that CUDA uses. This is required to appropriately develop software to optimally take advantage of GPU resources.
5 Stunden zum Abschließen
11 Videos (Gesamt 57 min), 1 Lektüre, 1 Quiz
Über den Spezialisierung GPU Programming
This specialization is intended for data scientists and software developers to create software that uses commonly available hardware. Students will be introduced to CUDA and libraries that allow for performing numerous computations in parallel and rapidly. Applications for these skills are machine learning, image/audio signal processing, and data processing.
Häufig gestellte Fragen
Wann erhalte ich Zugang zu den Vorträgen und Aufgaben?
Was bekomme ich, wenn ich diese Spezialisierung abonniere?
Ist finanzielle Unterstützung möglich?
Can I program on my own desktop/laptop
Haben Sie weitere Fragen? Besuchen Sie das Learner Help Center.
