Einblicke, Tutorials und Neuigkeiten von unserem Team
I'll discuss this from several angles: What is HAMi, and how does it fundamentally differ from NVIDIA's solutions? Why doesn't NVIDIA do it? Is it a technical limitation or a business decision? What are HAMi's core competitiveness and long-term moat?
This article analyzes how Hygon DCU devices can be virtualized through HAMi to achieve unified management and scheduling.
In this article, we analyze HAMi's scheduling feature: fine-grained scheduling based on GPU type and even UUID.
HAMi v2.5.0 is released! It adds dynamic MIG support and brings significant improvements in stability and usability. Come and see what's new.
This is the fifth article in the HAMI principle analysis series, providing a simple analysis of the working principles of HAMI-Core, including how it takes effect, how CUDA APIs are intercepted, and how it implements resource limits for GPU core and memory.
This is the fourth article in the HAMI principle analysis series, analyzing how hami-scheduler selects nodes during scheduling, i.e., how advanced scheduling strategies like Spread and Binpack are implemented.
This is the third article in the HAMI principle analysis series, analyzing the hami-scheduler workflow.
In the last article, we analyzed hami-device-plugin-nvidia and understood how HAMI's NVIDIA device plugin works. This is the second article in the HAMI principle analysis series, analyzing the implementation of hami-scheduler.
This is the first article in a series analyzing the implementation principles of the open-source vGPU solution HAMI, focusing on the hami-device-plugin-nvidia.
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