Volcano: Running AI/DL workload on Kubernetes
Kubernetes started as a general purpose orchestration framework with a focus on serving jobs. But as it gains popularity, users want to run AI/DL workloads on Kubernetes, such as TensorFlow, PyTorch e …
| Talk Title | Volcano: Running AI/DL workload on Kubernetes |
| Speakers | Da Ma (Software Architect, Huawei) |
| Conference | KubeCon + CloudNativeCon |
| Conf Tag | |
| Location | Shanghai, China |
| Date | Jun 23-26, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Kubernetes started as a general purpose orchestration framework with a focus on serving jobs. But as it gains popularity, users want to run AI/DL workloads on Kubernetes, such as TensorFlow, PyTorch etc. When running these workloads on Kubernetes, several advanced capability are required, e.g. fair-share sharing, queue, job management (suspend/resume), data management. This talk will demonstrate how to use volcano to bring “batch” capability.
