Provides function distributed programming, supporting languages such as Python, Java, and C++, enabling high-performance distributed execution akin to single-machine programming.
Provide large-scale distributed dynamic scheduling, support rapid elastic scaling and cross-node migration of function instances, and achieve efficient utilization of cluster resources.
Provide heterogeneous distributed multi-level caching, support Object and Stream semantics, enabling high-performance data sharing and transfer between function instances.
Compatible with the core interfaces of the open-source software Ray, it facilitates the seamless migration of workloads running on Ray (such as vllm/verl, etc.) to the Yuanrong cluster, while also enjoying the performance advantages brought by Yuanrong's deep optimization on Huawei Kunpeng and Ascend hardware.
Provide large-scale distributed dynamic scheduling, support rapid elastic scaling and cross-node migration of function instances, and achieve efficient utilization of cluster resources.
Contributions last year: 152
Max continuous contributions: 6
Recent contributions: 1
Commits, issues, and pull requests will appear on your contribution graph. Only when the email address used for the commits in local configuration is associated with your GitOSC account, the commits' contribution will be counted.
