  Heterogeneous chiplets have been proposed for accelerating high-performance
computing tasks. Integrated inside one package, CPU and GPU chiplets can share
a common interconnection network that can be implemented through the
interposer. However, CPU and GPU applications have very different traffic
patterns in general. Without effective management of the network resource, some
chiplets can suffer significant performance degradation because the network
bandwidth is taken away by communication-intensive applications. Therefore,
techniques need to be developed to effectively manage the shared network
resources. In a chiplet-based system, resource management needs to not only
react in real-time but also be cost-efficient. In this work, we propose a
reconfigurable network architecture, leveraging Kalman Filter to make accurate
predictions on network resources needed by the applications and then adaptively
change the resource allocation. Using our design, the network bandwidth can be
fairly allocated to avoid starvation or performance degradation. Our evaluation
results show that the proposed reconfigurable interconnection network can
dynamically react to the changes in traffic demand of the chiplets and improve
the system performance with low cost and design complexity.
