Many emerging Artificial Intelligence (AI) applications require on-demand provisioning of large-scale computing, which can only be enabled by leveraging distributed computing services interconnected through networking. To address such increasing demand for networking to serve AI tasks, we investigate new scheduling strategies to improve communication efficiency and test them on a programmable testbed. We also show relevant challenges and research directions.

翻译：许多新兴人工智能应用需要大规模计算资源的按需供给，这只能通过利用网络互连的分布式计算服务来实现。为应对人工智能任务对网络服务日益增长的需求，我们研究了提升通信效率的新型调度策略，并在可编程测试平台上进行了验证。同时，我们展示了相关挑战与研究方向。