A U nified, L ow-overhead F ramework to Support Continuous Profiling and Optimization

A Unified, Low-overhead Framework to Support Continuous Profiling and Optimization

Xubin (Ben) He ([email protected])

Storage Technology & Architecture Research(STAR) Lab

Department of Electrical and Computer Engineering

22nd IEEE International Performance Computing and Communications Conference (IPCCC’2003)

ULF Storage Technology & Architecture Research lab(STAR) T.T.U 2

Outline

Introduction Architecture and Design Performance Evaluations Conclusions and Future Work


Introduction


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.


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


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


Introduction Architecture and Design

Performance EvaluationsConclusions and Future Work


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


ULF Board

Low cost, low power embedded processor.

Expandable with secondary PCI slot. Interface with host via standard PCI slot


Interaction between Plug-ins and Boards

Initial stage-->Running--->Cleanup


Example Applications

Low overhead profiling

On-line program optimizer

On-line file system cache optimizer

…


IntroductionArchitecture and Design

Performance EvaluaitonsConclusions and Future Work


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


PostMark Results


Different W/R ratio


Iozone results


IntroductionArchitecture and DesignPerformance Evaluations

Conclusions and Future Work


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%.


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


Acknowledgements

Dr. Ken Yang Ming Zhang

NSF Manufacturing Center at T.T.U

Xubin He ([email protected])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

A U nified, L ow-overhead F ramework to Support Continuous Profiling and Optimization

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