@wolfbolin
WolfBolin 暂无简介
Provide large-scale distributed dynamic scheduling, support rapid elastic scaling and cross-node migration of function instances, and achieve efficient utilization of cluster resources.
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.
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 heterogeneous distributed multi-level caching, support Object and Stream semantics, enabling high-performance data sharing and transfer between function instances.