arXiv subjects

Stanko Novaković

Publications and source records attributed to Stanko Novaković.

2 recordsLinked to original sources

arXiv2025

Wave: Offloading Resource Management to SmartNIC Cores

SmartNICs are increasingly deployed in datacenters to offload tasks from server CPUs, improving the efficiency and flexibility of datacenter security, networking and storage. Optimizing cloud server efficiency in this way is critically important to ensure that virtually all server resources are available to paying customers. Userspace system software, specifically, decision-making tasks performed by various operating system subsystems, is particularly well suited for execution on mid-tier SmartNIC ARM cores. To this end, we introduce Wave, a framework for offloading userspace system software to processes/agents running on the SmartNIC. Wave uses Linux userspace systems to better align system functionality with SmartNIC capabilities. It also introduces a new host-SmartNIC communication API that enables offloading of even $μ$s-scale system software. To evaluate Wave, we offloaded preexisting userspace system software including kernel thread scheduling, memory management, and an RPC stack to SmartNIC ARM cores, which showed a performance degradation of 1.1%-7.4% in an apples-to-apples comparison with on-host implementations. Wave recovered host resources consumed by on-host system software for memory management (saving 16 host cores), RPCs (saving 8 host cores), and virtual machines (an 11.2% performance improvement). Wave highlights the potential for rethinking system software placement in modern datacenters, unlocking new opportunities for efficiency and scalability.

cs.OS↗

arXiv2025

Coach: Exploiting Temporal Patterns for All-Resource Oversubscription in Cloud Platforms

Cloud platforms remain underutilized despite multiple proposals to improve their utilization (e.g., disaggregation, harvesting, and oversubscription). Our characterization of the resource utilization of virtual machines (VMs) in Azure reveals that, while CPU is the main underutilized resource, we need to provide a solution to manage all resources holistically. We also observe that many VMs exhibit complementary temporal patterns, which can be leveraged to improve the oversubscription of underutilized resources. Based on these insights, we propose Coach: a system that exploits temporal patterns for all-resource oversubscription in cloud platforms. Coach uses long-term predictions and an efficient VM scheduling policy to exploit temporally complementary patterns. We introduce a new general-purpose VM type, called CoachVM, where we partition each resource allocation into a guaranteed and an oversubscribed portion. Coach monitors the oversubscribed resources to detect contention and mitigate any potential performance degradation. We focus on memory management, which is particularly challenging due to memory's sensitivity to contention and the overhead required to reassign it between CoachVMs. Our experiments show that Coach enables platforms to host up to ~26% more VMs with minimal performance degradation.

cs.OS↗