Performance Evaluation of Load Sharing Policies on a Beowulf Cluster

1
Performance Evaluation of Load Sharing Policies
on a Beowulf Cluster

• James Nichols
• Marc Lemaire
• Advisor Mark Claypool

2
Outline

• Introduction
• Methodology
• Results
• Conclusions

3
Introduction

• What is a Beowulf cluster?
• Cluster of computers networked together via
  Ethernet
• Load Distribution
• Share load, decreasing response times and
  increasing overall throughput
• Need for expertise in a particular load
  distribution mechanism
• Load
• Historically use CPU as the load metric.
• What about disk and memory load? Or system
  events like interrupts and context switches?
• PANTS Application Node Transparency System
• Removes the need for expertise required by other
  load distribution mechanisms

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PANTS

• PANTS Application Node Transparency System
• Developed in previous MQP CS-DXF-9918. Enhanced
  the following year to use DIPC in CS-DXF-0021
• Intercepts execve() system calls
• Uses /proc files system to calculate CPU load to
  classify node as busy or free
• Any workload which does not generate CPU load
  will not be distributed
• Near linear speedup for computationally intensive
  applications
• New load metrics and polices!

5
Outline

• Introduction
• Methodology
• Results
• Conclusions

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Methodology

• Identified load parameters
• Implemented ways to measure parameters
• Improved PANTS implementation
• Built micro benchmarks which stressed each load
  metric
• Built macro benchmark which stressed a more
  realistic mix of metrics
• Selected real world benchmark

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Methodology Load Metrics

• Acquired via /proc/stat
• CPU Totals jiffies (1/100ths of a second) that
  the processor spent on user, nice, and system
  processes. Obtain a percentage of total.
• I/O Blocks read/written to disk per second.
• Memory Page operations per second. Example a
  virtual memory page fault requiring a page to be
  loaded into memory from disk
• Interrupts System interrupts per second.
  Example incoming Ethernet packet.
• Context Switches How many times the processor
  switched between processes per second.

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Methodology Micro Macro Benchmarks

• Implemented micro and macro benchmarks
• Helped refine understanding of how the system was
  performing, tested our load metrics, etc.
• (Not enough time to present)

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Real world benchmark Linux kernel compile

• Distributed compilation of the Linux kernel
• Executed by the standard Linux program make
• Loads I/O and memory resources
• Details
• Kernel version 2.4.18
• 432 files
• Mean source file size 19KB
• Needed to expand relative path names to full
  paths
• Thresholds
• Pants default CPU 95
• New policy CPU 95, I/O 1000 Blocks/sec,
  Memory 4000 Page faults/sec, IRQ 115000
  interrupts/sec, Context Switches 6000
  switches/sec
• Compare PANTS default policy to our new load
  metrics and policy

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Outline

• Introduction
• Methodology
• Results
• Conclusions

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Results CPU
12
Results Memory
13
Results Context Switches
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Results Summary
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Conclusions

• Achieve better throughput and more balanced load
  distribution when metrics include I/O, memory,
  interrupts, and context switches.
• Future Work
• Use preemptive migration?
• Include network usage load metric.
• For more information visit http//pants.wpi.edu
• Questions?