Optimizing Main Memory Usage in Modern Computing Systems to Improve Overall System Performance

Authors

Daniel Jose Campello, Florida International UniversityFollow

Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Major/Program

Computer Science

First Advisor's Name

Raju Rangaswami

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Giri Narasimhan

Second Advisor's Committee Title

Committee Member

Third Advisor's Name

Jason Liu

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Gang Quan

Fourth Advisor's Committee Title

Committee Member

Fifth Advisor's Name

Ming Zhao

Fifth Advisor's Committee Title

Committee Member

Keywords

operating systems, storage, persistent memory, clustering, virtual machine, caching, memory, tiering, asynchronous I/O, system performance

Date of Defense

6-20-2016

Abstract

Operating Systems use fast, CPU-addressable main memory to maintain an application’s temporary data as anonymous data and to cache copies of persistent data stored in slower block-based storage devices. However, the use of this faster memory comes at a high cost. Therefore, several techniques have been implemented to use main memory more efficiently in the literature. In this dissertation we introduce three distinct approaches to improve overall system performance by optimizing main memory usage.

First, DRAM and host-side caching of file system data are used for speeding up virtual machine performance in today’s virtualized data centers. The clustering of VM images that share identical pages, coupled with data deduplication, has the potential to optimize main memory usage, since it provides more opportunity for sharing resources across processes and across different VMs. In our first approach, we study the use of content and semantic similarity metrics and a new algorithm to cluster VM images and place them in hosts where through deduplication we improve main memory usage.

Second, while careful VM placement can improve memory usage by eliminating duplicate data, caches in current systems employ complex machinery to manage the cached data. Writing data to a page not present in the file system page cache causes the operating system to synchronously fetch the page into memory, blocking the writing process. In this thesis, we address this limitation with a new approach to managing page writes involving buffering the written data elsewhere in memory and unblocking the writing process immediately. This buffering allows the system to service file writes faster and with less memory resources.

In our last approach, we investigate the use of emerging byte-addressable persistent memory technology to extend main memory as a less costly alternative to exclusively using expensive DRAM. We motivate and build a tiered memory system wherein persistent memory and DRAM co-exist and provide improved application performance at lower cost and power consumption with the goal of placing the right data in the right memory tier at the right time. The proposed approach seamlessly performs page migration across memory tiers as access patterns change and/or to handle tier memory pressure.

Identifier

FIDC000755

ORCID

orcid.org/0000-0002-3409-6405

Recommended Citation

Campello, Daniel Jose, "Optimizing Main Memory Usage in Modern Computing Systems to Improve Overall System Performance" (2016). FIU Electronic Theses and Dissertations. 2568.
https://digitalcommons.fiu.edu/etd/2568