Cloud Based Datacenter Network Acceleration Using FPGA for Data-Offloading

Currently, the high performance processors in Spine-Leaf, Mesh, and Router layer-3 (SLMR-3) backend server domain have multiple cores, but data offloading from processor to the peripherials is not keeping pace with the required Quality of Service (QoS) needed to balance the workload on a Warehouse Scaled Computer (WSC) running a developed Enterprise Energy Tracking Analytic Cloud Portal (EETACP) datacenter network. High speed with low latency interconnects between the processors and Field Programmable Gate Array (FPGA) is critical for achieving performance benefits in EETACP deployment. Most of the servers in WSC architectures are running at average utilization rates and perform well under peak processing power. These servers are good candidates for FPGA processors in cloud based datacenters owing to its acceleration coherency. This paper made a strong case for cloud based support for EETACP.  An FPGA based Spine-Leaf model is proposed to be an attractive alternative to replacing traditional network models for EETACP provisioning. The work analysed reconfigurable FPGAs, characterized a simplified process model for hyperscaler FPGA cloud network description. To validate the design performance, comparisons were made with two similar networks namely DCell and BCube for enterprise application deployments. The results validates FPGA based DCN acceleration for QoS experience in  cloud based EETACP.