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22nd IEEE International Performance Computing and Communications Conference (IPCCC’2003). A U nified, L ow-overhead F ramework to Support Continuous Profiling and Optimization. Xubin (Ben) He (hexb@tntech.edu) Storage Technology & Architecture Research( STAR ) Lab - PowerPoint PPT Presentation
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A Unified, Low-overhead Framework to Support Continuous Profiling and Optimization
Xubin (Ben) He (hexb@tntech.edu)
Storage Technology & Architecture Research(STAR) Lab
Department of Electrical and Computer Engineering
22nd IEEE International Performance Computing and Communications Conference (IPCCC’2003)
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Outline
Introduction Architecture and Design Performance Evaluations Conclusions and Future Work
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Introduction
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Motivations
System profiling is an important mechanism to observe system activities.
Profiling-based optimization has become a key technique.
Continuous and online optimization is needed because of changed system usage patterns.
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Current State-of-the-art
Traditional approaches bring high overhead to already overloaded system.
Profiling and optimization overhead: Raw Data Gathering Data Recording Data Processing Feedback
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Introducing Unified, Low-overhead Framework (ULF)
Offload computing overheads from host processors to an embedded processor;
Continuous feedback loop model: 1. Low overhead profiling to gather system event
data; 2. Parallel processing raw data and policy
generation; 3. Apply policy to host;
HostULF
1
2
3
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Introduction Architecture and Design
Performance EvaluationsConclusions and Future Work
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Components
ULF board: an embedded processor with a sufficient amount of RAM
Host-side module: APIs as a library or kernel module
Board-side module:embedded os, a libray, plug-ins
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ULF Board
Low cost, low power embedded processor.
Expandable with secondary PCI slot. Interface with host via standard PCI slot
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Interaction between Plug-ins and Boards
Initial stage-->Running--->Cleanup
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Example Applications
Low overhead profiling
On-line program optimizer
On-line file system cache optimizer
…
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IntroductionArchitecture and Design
Performance EvaluaitonsConclusions and Future Work
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Experimental Setup
Methodology Prototype using Intel IOP310 processor, Linux 2.4.16 I/O profiling tool: LTT(Linux Trace Toolkit)
Workloads Postmark of Network Appliances: throughput
20k initial files, transactions ranging from 150k to 300k. Iozone
4 configurations1) NTNR: Neither Traced Nor Recorded2) TNR: Traced but Not Recorded3) TDR: Traced and Disk Recorded4) TFR: Traced and ULF Recorded
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PostMark Results
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Different W/R ratio
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Iozone results
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IntroductionArchitecture and DesignPerformance Evaluations
Conclusions and Future Work
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Conclusions
A unified, low-overhead framework helps profiling tools to save profiling data rapidly and perform run-time parallel processing.
Reduces profiling overhead LTT: 40%-->0.4%.
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Future Work
Apply ULF to more case studies Performance:
Adaptively adjust system prefetching and caching policy;
Online code rewrite and recompilation; Security:
Monitor abnormal system access and high risk events.
Intrusion detection
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Acknowledgements
Dr. Ken Yang Ming Zhang
NSF Manufacturing Center at T.T.U
Xubin He (hexb@tntech.edu)http://www.ece.tntech.edu/hexb/starlab.htm
Storage Technology & Architecture Research(STAR) Lab
Department of Electrical and Computer Engineering
A Unified, Low-overhead Framework to Support Continuous Profiling and Optimization
IPCCC’2003
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