  Semantic communication has shown great potential in boosting the
effectiveness and reliability of communications. However, its systems to date
are mostly enabled by deep learning, which requires demanding computing
resources. This article proposes a framework for the computing networks enabled
semantic communication system, aiming to offer sufficient computing resources
for semantic processing and transmission. Key techniques including semantic
sampling and reconstruction, semantic-channel coding, semantic-aware resource
allocation and optimization are introduced based on the cloud-edge-end
computing coordination. Two use cases are demonstrated to show advantages of
the proposed framework. The article concludes with several future research
directions.
