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Explore the challenges and solutions for managing heterogeneous AI infrastructure in Kubernetes clusters through this informative conference talk. Delve into the HAMi project, designed to address the complexities of integrating diverse AI devices such as NVIDIA, Intel, and Huawei Ascend. Learn how to improve resource utilization, implement unified scheduling and observability, and enhance GPU sharing capabilities. Discover flexible scheduling strategies for GPUs, including NUMA affinity/anti-affinity and binpack/spread options. Gain insights into integrating HAMi with other projects like Volcano and scheduler-plugin. Examine real-world case studies from production-level users and discuss ongoing challenges and future roadmap for heterogeneous AI infrastructure management in Kubernetes environments.
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