Kabir, Rashadul, authorKim, Ryan G., authorNikdast, Mahdi, authorACM, publisher2024-11-112024-11-112023-11-12Rashadul Kabir, Ryan G. Kim, and Mahdi Nikdast. 2023. RISA: Round-Robin Intra-Rack Friendly Scheduling Algorithm for Disaggregated Datacenters. In Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W 2023), November 12–17, 2023, Denver, CO, USA. ACM, New York, NY, USA, 9 pages. https://doi.org/10.1145/3624062.3624228https://hdl.handle.net/10217/239523Recent trends see a move away from a fixed-resource server-centric datacenter model to a more adaptable "disaggregated" datacenter model. These disaggregated datacenters can then dynamically group resources to the specific requirements of an incoming workload, thereby improving efficiency. To properly utilize these disaggregated datacenters, workload allocation techniques must examine the current state of the datacenter and choose resources that not only optimize the current workload request, but future ones. Since disaggregated datacenters are severely bottlenecked by the available network resources, our work proposes a heuristic-based approach called RISA, which significantly reduces the network usage of workload allocations in disaggregated datacenters. Compared to the state-of-the-art, RISA reduces the power consumption for optical components by 33% and reduces the average CPU-RAM round-trip latency by 50%. Additionally, RISA significantly outperforms the state-of-the-art in terms of execution time.born digitalarticleseng© Rashadul Kabir, et al. | ACM 2023. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SC-W '23, https://dx.doi.org/10.1145/3624062.3624228.disaggregated/composable data centersnetwork-aware schedulingenergy-aware schedulingload balancingTexthttps://doi.org/10.1145/3624062.3624228