High Volume Computing: Identifying and Characterizing Throughput Oriented Workloads in Data Centers

Provided by: Cornell University
Topic: Data Centers
Format: PDF
For the first time, this paper systematically identifies three categories of throughput oriented workloads in data centers: services, data processing applications, and interactive real-time applications, whose targets are to increase the volume of throughput in terms of processed requests or data, or supported maximum number of simultaneous subscribers, respectively, and the authors coin a new term high volume computing (in short HVC) to describe those workloads and data center computer systems designed for them. They characterize and compare HVC with other computing paradigms, e.g., high throughput computing, warehouse-scale computing, and cloud computing, in terms of levels, workloads, metrics, coupling degree, data scales, and number of jobs or service instances.

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