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MTDA: Efficient and Fair DPU Offloading Method for Multiple Tenants
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AI
DOI：10.1109/TSC.2024.3433588.png)
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Abstract
En 中文
In modern cloud computing environment, the offloading potential of DPU must be fully exploited for multiple tenants. Existing DPU offloading techniques lack the capability to perform the fair allocation of a DPU domain's internal resources among tenants with various performance requirements. In this article, we propose a virtual multi-channel DPU offloading architecture for multiple tenants (MTDA) and implement it on a BlueField-2 DPU platform to achieve stability and fairness in resource allocation for generic datacenter tasks. MTDA provides an independent virtual channel for each tenant before their requests are submitted to avoid competition among tenants. Considering the diverse requirements of tenants, MTDA constructs a credit-based resource allocation model and a traffic-aware scheduling algorithm to fully utilize the rich computing resources of DPU and improve the fairness of DPU resource allocation. Experimental results show that MTDA increases the throughput by up to 101.2%, 143.2%, 36.1%, and 41.7%, lowers the latency by up to 50.3%, 58.9%, 26.6%, and 29.4%, improves the fairness by up to 98.8%, 99.0%, 98.3%, and 98.4%, and provides more stable performance for multi-tenants, compared with DPDK, iPipe, FairNIC, and LogNIC.
Keywords:
Credit model
DPU
fair resource allocation
multi-tenant
Credit model
DPU
fair resource allocation
multi-tenant
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