Ph.D. Alumni: Reza Azimi

Reference:

Reza Azimi
System Software Utilization of Hardware Performance Monitoring Information
Ph.D. Thesis, Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada, 2007.

Supervisor(s):

Michael Stumm

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Abstract:

Over the last several decades, microprocessors have evolved to assist system software in implementing new functionality or in improving the performance of programs. The relative abundance of available silicon may further motivate introducing new hardware features other than those that are directly required for executing code. The main focus of this dissertation is on how new hardware support can collect accurate performance data so as to enable system software in making more informed decisions in improving the performance of programs.

First, we explore the problem of using Hardware Performance Counters (HPCs) to identify CPU bottlenecks accurately and efficiently. We address the problem of having a limited number of available HPCs by developing fine-grained HPC multiplexing that provides a large set of logical HPCs. We develop a simple and useful performance model, called stall breakdown, to identify stressed processor components by focusing on cycles where the instruction completion stops. We generate the stall breakdown model using HPC multiplexing online with negligible overhead.

Secondly, we explore different methods of fine-grained data sampling at the hardware level. Using the continuous data sampling features of the IBM Power5 processor, we identify a new technique to produce data samples based on their source, and in a case study, we demonstrate how to use source-based data samples to accurately characterize data sharing patters among concurrent threads to effectively support sharing-aware schedulers.

Finally, we propose novel hardware to track memory accesses at the granularity of virtual pages. Our proposed hardware is simple, efficient, and generic. We show how the proposed page access tracking hardware (PATH) can be used to improve performance in three different areas of memory management. in all three cases, we show that significant performance improvement can be achieved with negligible software overhead.

Keywords:

Operating systems, Computer architecture, performance monitoring, hardware performance monitors, hardware performance counters, multiplexing, stall breakdown, data sampling, page access tracking, memory management

BibTeX:

@phdthesis(Azimi-PhD07,
    author = {Reza Azimi},
    title = {System Software Utilization of Hardware Performance Monitoring Information},
    school = {Department of Electrical and Computer Engineering, University of Toronto},
    address = {Toronto, Canada},
    supervisors = {Michael Stumm},
    year = {2007},
    keywords = {Operating systems, Computer architecture, performance monitoring, hardware performance monitors, hardware performance counters, multiplexing, stall breakdown, data sampling, page access tracking, memory management}
)