We choose eleven representative data analysis workloads and characterize their micro-architectural characteristics by using hardware performance counters.
Aug 6, 2024 · Data analysis applications play a significant role in data centers, and hence it has became increasingly important to understand their behaviors ...
The study on the workloads reveals that data analysis applications share many inherent characteristics, which place them in a different class from desktop, ...
As the amount of data explodes rapidly, more and more corporations are using data centers to make effective decisions and gain a competitive edge.
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In this paper, we use data traces obtained from a real data center to develop such capabilities. First, we search for repeatable workload patterns by exploring ...
Apr 4, 2024 · In this paper, we present a comprehensive data-driven analysis of a production cloud data center. We monitor and collect the physical machine-level metrics.
In this paper, we present a comprehensive data- driven analysis of a production cloud data center. We monitor and collect the physical machine-level metrics ...
We use a trace based approach for capacity management that relies on i) the characterization of workload demand patterns, ii) the generation of synthetic.
Abstract—Warehouse-scale cloud datacenters co-locate work- loads with different and often complementary characteristics for improved resource utilization.
To address this problem, in this work we collect and analyze a 6-month Spark workload from a major provider of big data processing services, Databricks. Our ...