Overall Objectives
Research Program
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Memory management for big data

Participants : Antoine Blin, Damien Carver, Maxime Lorrillere, Sébastien Monnet, Julien Sopena [correspondent] .

Automated file cache pooling

Some applications, like online sales servers, intensively use disk I/Os. Their performance is tightly coupled with I/Os efficiency. To speed up I/Os, operating systems use free memory to offer caching mechanisms. Several I/O intensive applications may require a large cache to perform well. However, nowadays resources are virtualized. In clouds, for instance, virtual machines (VMs) offer both isolation and flexibility. This is the foundation of cloud elasticity, but it induces fragmentation of the physical resources, including memory. This fragmentation reduces the amount of available memory a VM can use for caching I/Os. Previously, we proposed Puma (for Pooling Unused Memory in Virtual Machines) which allows I/O intensive applications running on top of VMs to benefit of large caches. This was realized by providing a remote caching mechanism that provides the ability for any VM to extend its cache using the memory of other VMs located either in the same or in a different host.

We have performed an extensive evaluation of Puma [53] and we have enhanced our solution: Puma adapts automatically the amount a memory that a VM offers to another VM. Furthermore, if the network becomes overloaded, Puma detects a performance degradation and stops using a remote cache.