相关论文: Acila: Attaching Identities of Workloads for Effic…

Workloads in modern cloud data centers are becoming increasingly complex. The number of workloads running in cloud data centers has been growing exponentially for the last few years, and cloud service providers (CSP) have been supporting…

Warehouse-scale cloud datacenters co-locate workloads with different and often complementary characteristics for improved resource utilization. To better understand the challenges in managing such intricate, heterogeneous workloads while…

The Cloud Computing paradigm consists in providing customers with virtual services of the quality which meets customers' requirements. A cloud service operator is interested in using his infrastructure in the most efficient way while…

Capability jobs (e.g., large, long-running tasks) and capacity jobs (e.g., small, short-running tasks) are two common types of workloads in high-performance computing (HPC). Different HPC systems are typically deployed to handle distinct…

The proliferation of the Internet of Things (IoT) has introduced a massive influx of devices into the market, bringing with them significant security vulnerabilities. In this diverse ecosystem, robust IoT device identification is a critical…

Hosting database services on cloud systems has become a common practice. This has led to the increasing volume of database workloads, which provides the opportunity for pattern analysis. Discovering workload patterns from a business logic…

Networked applications traditionally derive their identity from the identity of the host on which they run. The default application identity acquired from the host results in subtle and substantial problems related to application…

AI-based monitoring has become crucial for cloud-based services due to its scale. A common approach to AI-based monitoring is to detect causal relationships among service components and build a causal graph. Availability of domain…

The evolving necessity of the Internet increases the demand on the bandwidth. Therefore, this demand opens the doors for the hackers' community to develop new methods and techniques to gain control over networking systems. Hence, the…

Hyperscalars run services across a large fleet of servers, serving billions of users worldwide. These services, however, behave differently than commonly available benchmark suites, resulting in server architectures that are not optimized…

In modern server CPUs, the Last-Level Cache (LLC) serves not only as a victim cache for higher-level private caches but also as a buffer for low-latency DMA transfers between CPU cores and I/O devices through Direct Cache Access (DCA).…

We present and formalize a general approach for profiling workload by leveraging only a priori available static metadata to supply appropriate resource needs. Understanding the requirements and characteristics of a workload's runtime is…

The increasing prominence of AI necessitates the deployment of inference platforms for efficient and effective management of AI pipelines and compute resources. As these pipelines grow in complexity, the demand for distributed serving rises…

Isolation is a critical property for shared infrastructure to limit exposure and interference among simultaneous running workloads. Cloud providers use different isolation mechanisms such as full Virtual Machines, microVMs, Linux…

In this paper we show that the data plane of commodity programmable (Network Interface Cards) NICs can run neural network inference tasks required by packet monitoring applications, with low overhead. This is particularly important as the…

In the recent past, characterizing workloads has been attempted to gain a foothold in the emerging serverless cloud market, especially in the large production cloud clusters of Google, AWS, and so forth. While analyzing and characterizing…

Clouds inherit CPU scheduling policies of operating systems. These policies enforce fairness while leveraging best-effort mechanisms to enhance responsiveness of all schedulable entities, irrespective of their service level objectives…

This paper proposes a conceptual model for a secure and performance-efficient workload management model in cloud environments. In this model, a resource management unit is employed for energy and performance proficient allocation of virtual…

In warehouse-scale cloud datacenters, co-locating online services and offline batch jobs is an efficient approach to improving datacenter utilization. To better facilitate the understanding of interactions among the co-located workloads and…

Aggregating neighbor features is essential for point cloud classification. In the existing work, each point in the cloud may inevitably be selected as the neighbors of multiple aggregation centers, as all centers will gather neighbor…