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—MapReduce is a data-driven programming model proposed by Google in 2004 which is especially well suited for distributed data analytics applications. We consider the management of MapReduce applications in an environment where multiple applications share the same physical resources. Such sharing is in line with recent trends in data center management which(More)
The performance of large applications tends to be poor due to the high overhead added by the swapping mechanism. The same problem may be found in highly-loaded multi-programmed systems where many of the running applications have to use the swap space in order to be able to execute at the same time. Furthermore, those large applications might not be able to(More)
—Virtualized infrastructure providers demand new methods to increase the accuracy of the accounting models used to charge their customers. Future data centers will be composed of many-core systems that will host a large number of virtual machines (VMs) each. While resource utilization accounting can be achieved with existing system tools, energy accounting(More)
Virtualized infrastructure providers demand new methods to increase the accuracy of the accounting models used to charge their customers. Future data centers will be composed of many-core systems that will host a large number of virtual machines (VMs) each. While resource utilization accounting can be achieved with existing system tools, energy accounting(More)
This paper introduces the work being carried out at Barcelona Supercomputing Center in the area of Green Computing. We have been working in resource management for a long time and recently we included the energy parameter in the decision process, considering that for a more sustainable science, the paradigm will shift from " time to solution " to " kWh to(More)
We present a resource-aware scheduling technique for MapRe-duce multi-job workloads that aims at improving resource utilization across machines while observing completion time goals. Existing MapRe-duce schedulers define a static number of slots to represent the capacity of a cluster, creating a fixed number of execution slots per machine. This abstraction(More)
—Next generation data centers will be composed of thousands of hybrid systems in an attempt to increase overall cluster performance and to minimize energy consumption. New programming models, such as MapReduce, specifically designed to make the most of very large infrastructures will be leveraged to develop massively distributed services. At the same time,(More)
In order to evaluate the goodness of parallel systems, it is necessary to know how parallel programs behave. The SPLASH-2 applications provide us a realistic workload for such systems. So, we have made different implementations of the PARMACS macros used by SPLASH-2 applications, based on several execution and synchronization models, from classical Unix(More)
SUMMARY The performance of memory-intensive applications tends to be poor due to the high overhead added by the swapping mechanism. The same problem may be found in highly-loaded multi-programming systems where all running applications have to use the swap space in order to be able to execute at the same time. In this paper, we present a solution to these(More)