HPC Vision in the Cloud is an advanced Smarter course from Örebro University on high-performance computing for computer-vision applications in cloud environments. You work with scalable architectures, parallel computing and GPU acceleration using technologies such as CUDA, Docker and Kubernetes. With tools for performance monitoring and resource optimisation, you learn to design energy-efficient, cloud-based solutions for complex vision problems. The course is given in English at distance with a few mandatory meetings on campus.
Duration: 3 months
Format: Hybrid
Location: Örebro
Language: English
Level: Advanced
Time commitment: About 80 hours over one term, part-time; distance with mandatory meetings
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About the course.
This certifies that the participant has developed expertise in high-performance computing (HPC) for computer vision applications in cloud environments. The participant understands scalable architectures, parallel computing, and GPU acceleration using technologies such as CUDA, Docker, and Kubernetes. Equipped with tools for performance monitoring and resource optimization, the participant can design energy-efficient, cloud-based solutions for complex vision problems that support sustainable digital innovation.
This certifies that the participant has developed expertise in high-performance computing (HPC) for computer vision applications in cloud environments. The participant understands scalable architectures, parallel computing, and GPU acceleration using technologies such as CUDA, Docker, and Kubernetes. Equipped with tools for performance monitoring and resource optimization, the participant can design energy-efficient, cloud-based solutions for complex vision problems that support sustainable digital innovation.
What you will learn
What you learn.
You can explain the principles of high-performance computing (HPC) for computer vision.
You can use parallel computing and GPU acceleration with e.g. CUDA.
You can build and run scalable solutions in the cloud with Docker and Kubernetes.
You can use tools for performance monitoring and resource optimisation.
You can design energy-efficient, cloud-based solutions for complex vision problems.
Curriculum
How the course is built.
HPC for computer vision
Scalable architectures and parallel computing for demanding vision tasks.
GPU acceleration
Using GPUs and CUDA to speed up vision computations.
Cloud-based deployment
Containerisation and orchestration with Docker and Kubernetes.
Performance and sustainability
Performance monitoring, resource optimisation and energy-efficient cloud solutions.
Target audience
Who is this for?
For professional engineers and developers who work with computer vision or cloud infrastructure and want to build scalable, energy-efficient HPC solutions. Prerequisites: 180 credits including 15 credits of programming, and English 5/English A.
What "verified" means here
Verified credential.
When you complete the course, Örebro universitet issues your certificate. Your name, the course content and the issue date are encrypted and secured on blockchain, so it cannot be changed, and anyone can check that it is genuine.
100% Verifiable certificates Secured on blockchain
