Resource Allocation Considering the Impact of Characteristics and Parallel Processing of Heterogeneous Computational Resources in Disaggregated Computing
Narunori Ebara, Saki Hatta, Yuta Ukon, Hiroyuki Uzawa, Shoko Ohteru, Shuhei Yoshida, Ken Nakamura · 2025
Data center operators are increasingly focusing on disaggregated computing to enhance resource utilization efficiency by pooling and logically connecting resources such as CPUs, memories, and accelerators. In disaggregated computing, data transfer between resources is fundamental for service execution. Conventional CPU-mediated data transfer often leads to communication bottlenecks due to data concentration. Therefore, direct data communication between heterogeneous computational resources is critical. To efficiently execute services through direct communication between heterogeneous computational resources, efficient allocation of computational resources and determination of routing paths should be done before service execution. In this paper, we propose a resource allocation method that effectively utilizes heterogeneous computational resources in disaggregated computing by modeling the impact of the characteristics of heterogeneous computational resources and parallel processing. Our method can derive the solution of this model in a practical amount of time. Simulation results show that the proposed method could decrease the number of resources by an average of 28% to 51% compared to the conventional method in a heterogeneous disaggregated computing system while meeting the service performance requirements.