With the fast development of big data systems in recent years, a variety of open-source
benchmarks have been built to evaluate and compare the workloads on these systems, and …

In recent years, there has been a convergence of Big Data (BD), High Performance
Computing (HPC), and Machine Learning (ML) systems. This convergence is due to the …

Modern data centers provide the foundational infrastructure of cloud computing. Workload
generation, which involves simulating or constructing tasks and transactions to replicate the …

Benchmarking is a traditional approach for system performance evaluation and optimization.
Over the past decades, a variety of file systems, eg, GFS, HDFS and Ceph, have been …

Modern latency-critical online services such as search engines often process requests by
consulting large input data spanning massive parallel components. Hence the tail latency of …

Recommender Systeme unterstützen aus einem Angebot von Diensten und Produkten auf
bspw. Verkaufs-oder Unterhaltungsplattformen, diejenigen zu finden, die die persönlichen …

Despite the importance of providing quick responsiveness to user requests for online
services, such request processing is very resource expensive when dealing with large-scale …

The trace analysis for datacenter holds a prominent importance for the datacenter
performance optimization. However, due to the error and low execution priority of trace …

We present a novel approach for accurate characterization of workloads. Workloads are
generally described with statistical models and are based on the analysis of resource …

With the growing size of the cloud data center, the high scheduling efficiency over massive-
scale cloud servers is hard to achieve, particularly when the scheduler requires the full real …