In this paper we explore the problem of automatically adjusting DBMS multiprogramming levels and memory allocations in order to achieve a set of per-class response time goals for a complex multiclass workload. We start by describing the phenomena that make this a very challenging problem

be deployed on a single computing node, realizing a multi-tenancy model. While virtualization and multitenancy are two sources of workload-execution overhead that have been studied in the past, we still need a thorough, empirical investigation of the joint impact of these overheads, on workload execution

In this paper we explore the problem of automatically adjusting DBMS multiprogramming levels and memory allocations in order to achieve a set of per-class msponse time goals for a complex multiclass wotkload. We start by describing the phenomena that make this a very challenging problem

The Internet is rapidly growing in number of users, traffic levels, and topological complexity. At the same time it is increasingly driven by economic competition. These developments render the characterization of network usage and workloads more difficult, and yet more critical. Few recent

Workstation clusters are being recognized as the main promising computing resource of the near future. A large size workstation cluster, consisting of locally connected workstations, has the power comparable to a supercomputer, at a fraction of the cost. Further, a wide area coupling of workstation clusters is not only suitable for exchange of mail and news or establishment of distributed information systems, but can also be exploited as a large metacomputer. The wide area distribution aspects will be covered in a separate paper by the E=MC 2 project [8]. This paper shows the potential power by characterizing the system and the needs of current applications, and outlines the general idea to efficiently utilize networks of workstation. The second part of the paper introduces the approach of the HiCon project to solve the operating system and programming environment problems that currently restrict proper exploitation of workstation clusters, and demonstrates the feasibility by real me...

of information on the performance requirements of commercial workloads, the lack of available applications for widespread study, and the fact that most representative applications are too large and complex to serve as suitable benchmarks for evaluating trade-offs in the design of processors and servers

... This paper identifies two challenges that machine simulators such as SimOS must overcome in order to effectively analyze large complex workloads: handling long workload execution times and collecting data effectively. To study long-running workloads, SimOS includes multiple interchangeable

The microprocessor industry is currently struggling with higher development costs and longer design times that arise from exceedingly complex processors that are pushing the limits of instructionlevel parallelism. Meanwhile, such designs are especially ill suited for important commercial

Acknowledgments

the machine is to be complete. Workload characterization: SimOS's ability to run complex, realistic workloads including commercial applications enables researchers to characterize workloads that have not been widely studied before. Examples include parallel compilations and the Sybase database. 9 ased