Multiple virtual machine (VM) workloads are increasingly com-mon, given the growth of managed enterprise application systems and consolidated virtual servers. Until now, there has been no prin-cipled approach to partitioning memory resource between multiple co-located VMs. In this paper, we develop a general framework for multi-VM heap sizing, based on the principle of utility maximiza-tion from microeconomic theory. We apply utility maximization to static heap sizing, and obtain performance improvements slightly better than current best-practice static heap sizing, and compara-ble with HotSpot ergonomics (current best-practice dynamic heap sizing). The major advantage of our approach is its simplicity and predictable resource utilization
(ENG) In this report we demonstrate the potential utility of resource allocation management systems ...
Abstract—Shared memory management is widely recognized as an optimization technique in the virtualiz...
Managing memory capacity in cloud environments is a challenging issue, mainly due to the temporal va...
Multiple virtual machine (VM) workloads are increasingly common, given the growth of managed enterpr...
In this position paper, we examine how economic theory can be applied to memory management. We obser...
We introduce the Forseti system, which is a principled ap-proach for holistic memory management. It ...
We propose a new, principled approach to adaptive heap sizing based on control theory. We review cur...
We propose a new, principled approach to adaptive heap sizing based on control theory. We review cur...
Heap size has a huge impact on the performance of garbage collected applications. A heap that barely...
Resource provisioning in compute clouds often requires an estimate of the capacity needs of Virtual ...
Abstract. Typical theorem-proving workloads on the Poly/ML runtime may execute for several hours, oc...
The Data allocation paradigm has become very popula r and useful tool since its introduction. Many l...
Limiting the amount of memory available to a program can hamstring its performance, however in a ga...
To date, virtual machine (VM) placement has traditionally been viewed as a bin packing problem where...
A virtual machine (VM) is a software abstraction of a real, physical machine. Virtualization has bee...
(ENG) In this report we demonstrate the potential utility of resource allocation management systems ...
Abstract—Shared memory management is widely recognized as an optimization technique in the virtualiz...
Managing memory capacity in cloud environments is a challenging issue, mainly due to the temporal va...
Multiple virtual machine (VM) workloads are increasingly common, given the growth of managed enterpr...
In this position paper, we examine how economic theory can be applied to memory management. We obser...
We introduce the Forseti system, which is a principled ap-proach for holistic memory management. It ...
We propose a new, principled approach to adaptive heap sizing based on control theory. We review cur...
We propose a new, principled approach to adaptive heap sizing based on control theory. We review cur...
Heap size has a huge impact on the performance of garbage collected applications. A heap that barely...
Resource provisioning in compute clouds often requires an estimate of the capacity needs of Virtual ...
Abstract. Typical theorem-proving workloads on the Poly/ML runtime may execute for several hours, oc...
The Data allocation paradigm has become very popula r and useful tool since its introduction. Many l...
Limiting the amount of memory available to a program can hamstring its performance, however in a ga...
To date, virtual machine (VM) placement has traditionally been viewed as a bin packing problem where...
A virtual machine (VM) is a software abstraction of a real, physical machine. Virtualization has bee...
(ENG) In this report we demonstrate the potential utility of resource allocation management systems ...
Abstract—Shared memory management is widely recognized as an optimization technique in the virtualiz...
Managing memory capacity in cloud environments is a challenging issue, mainly due to the temporal va...