Enabling Elastic Resource Management in Cloud FPGAs Via A Multi-layer Collaborative Approach.

This paper proposes a comprehensive solution for managing resources in cloud FPGAs from application programming to accelerator deployment, which are compatible with existing FPGA virtualization frameworks. To achieve this, we leverage Continuous Passing Style-based application programming templates and dynamic task graph-based software IR and compute resource pool-based hardware IR and Access/Execute Decoupled-based computation execution patterns. A preliminary experiment shows that our method is able to make full use of idle resources in FPGAs for computation, resulting in an nearly 40% reduction in average turnaround time.