For emerging datacenter (in short, DC) workloads, such as online Internet services or offline
data analytics, how to evaluate the upper bound performance and provide apple-to-apple …

For emerging datacenter (in short, DC) workloads, such as online Internet services or offline
data analytics, how to evaluate the upper bound performance and provide apple-to-apple …

All computing infrastructure suffers from performance variability, be it bare-metal or
virtualized. This phenomenon originates from many sources: some transient, such as noisy …

This paper presents the" isolate first, then share" OS model in which the processor cores,
memory, and devices are divided up between disparate OS instances and a new …

AI benchmarking provides yardsticks for benchmarking, measuring and evaluating
innovative AI algorithms, architecture, and systems. Coordinated by BenchCouncil, this …

While prior work has explored many proposed datacenter designs, only two designs, Clos-
based and expander-based, are generally considered practical because they can scale …

Traditional datacenter analysis is based on high-level, coarse-grained metrics. This
obscures our vision of datacenter behavior, as we do not observe the full picture nor …

As datacenters have proliferated over the last couple of decades and datacenter
applications have grown increasingly complex, two competing goals have emerged for …

In recent years, a number of benchmark suites have been created for the``Big Data''domain,
and a number of such applications fit the client-server paradigm. A large volume of recent …

Colocating multiple jobs on the same server has been widely applied for improving resource
utilization in cloud datacenters. However, the colocated jobs would contend for the shared …