Automated Reliability Classification of Queueing Models for - - PowerPoint PPT Presentation

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Automated Reliability Classification of Queueing Models for - - PowerPoint PPT Presentation

Jan 08, 2024 10 likes •264 views

Automated Reliability Classification of Queueing Models for Streaming Computation Jonathan Beard, Cooper Epstein, and Roger Chamberlain SBS Stream Based Supercomputing Lab http://sbs.wustl.edu Work also supported by: 1 Stream Processing

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SLIDE 1

Automated Reliability Classification of Queueing Models for Streaming Computation

Jonathan Beard, Cooper Epstein, and Roger Chamberlain

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Work also supported by:

1

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SLIDE 2

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Stream Processing

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for i←0 through N do a[i] ←(b[i] + c[i]) i++ end do

i++ a,b,c,i i <=N

a[i] ←(b[i] + c[i])

exit

Read b,c

  • ut <- b + c

Write a Traditional Control Flow Streaming

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SLIDE 3

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Stream Processing

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Kernel Assigned To Any Compute Resource

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SLIDE 4

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

RaftLib

C++ Streaming Template Library Auto-parallelizes code Manages resources, buffers, TCP links Automatically Optimized Online

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software download: http://raftlib.io

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SLIDE 5

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Modeling Streams as Queues

B C Q1 Q2

A

A B C “Stream” is modeled as a Queue

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SLIDE 6

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Buffer Sizing

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SLIDE 7

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Traditional Service Rate

Counter - In Counter - Out Isolated Compute Kernel

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V1 V2 s t

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SLIDE 8

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Example Streaming App

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Read Matrix Dot Product Dot Product Reduce Dot Product

1 i n

Matrix Multiply

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SLIDE 9

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Example Streaming App

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Rabin-Karp String Search

Rolling Hash Read File, Distribute Rolling Hash Rolling Hash Reduce Verify Match Verify Match

1 j i n 1

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SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

More Complex Example

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ID: 0 Name: AppVertex ID: 1 Name: AppVertex ID: 2 Name: AppVertex ID: 10 Name: AppVertex ID: 11 Name: AppVertex ID: 3 Name: AppVertex ID: 4 Name: AppVertex ID: 5 Name: AppVertex ID: 6 Name: AppVertex ID: 7 Name: AppVertex ID: 9 Name: AppVertex ID: 8 Name: AppVertex ID: 16 Name: AppVertex ID: 17 Name: AppVertex ID: 18 Name: AppVertex ID: 12 Name: AppVertex ID: 13 Name: AppVertex ID: 14 Name: AppVertex ID: 15 Name: AppVertex

Too Many Buffers to Manually Model

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SLIDE 11

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

“Knowledge” Transfer

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Machine Learning

“Knowledge”

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SLIDE 12

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Support Vector Machine

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Can we use a Support Vector Machine (SVM) to classify a model as use or don’t use?

B Q1

A

M/D/1 M/M/1

None

?

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SLIDE 13

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Features

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Kernel

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SLIDE 14

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Monitor Arrangement

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processor core processor core Kernel Thread Monitor Thread Kernel Thread processor core OS Scheduler Kernel A Kernel B Stream

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SLIDE 15

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Online Service Rate

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Rate Shift Here

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SLIDE 16

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Kernel

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Kernel

SVM

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SLIDE 17

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Applying the SVM

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SVM

B Q1

A

M/D/1 M/M/1 None

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SLIDE 18

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Training & Evaluation Methodology

> 45k micro-benchmark executions > 1,000 full application executions (2 apps) Multiple hardware types (ARM, x86, PowerPC) Multiple operating systems (Linux, OS X, BSD) Training / Testing

  • 20% of both micro-benchmark and

application data used for training

  • 80% used for testing

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SLIDE 19

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Test App 1

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Read Matrix Dot Product Dot Product Reduce Dot Product

1 i n

Matrix Multiply

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SLIDE 20

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Test App 2

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Rabin-Karp String Search

Rolling Hash Read File, Distribute Rolling Hash Rolling Hash Reduce Verify Match Verify Match

1 j i n 1

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SLIDE 21

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Correct Classification by M/M/1

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SLIDE 22

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Correct Classification by M/D/1

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SLIDE 23

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Test Classification Rates M/M/1

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Server Utilization

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SLIDE 24

SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

Test Classification Rates M/D/1

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Server Utilization

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SBS

Stream Based Supercomputing Lab

http://sbs.wustl.edu

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RaftLib: http://raftlib.io My Page: http://cse.wustl.edu/~beardj Lab Page: http://sbs.wustl.edu