Pipeline and Batch Sharing in Grid Workloads

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Pipeline and Batch Sharing in Grid Workloads

• Douglas Thain, John Bent, Andrea C.
  Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, and
  Miron Livny
• 2003
• Reviewed by Zhicheng Qiu

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Overview

• What they want to do?
• Characterizes workloads composed of pipelines of
  sequential processes
• How they doing?
• measurements of the memory, CPU, and I/O
  requirements of individual components
• analyses of I/O sharing within complete batches.
• It has no relation to the scheduling

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Pipeline Batch Sharing
How the Pipeline and Batch Sharing work?
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Workloads categories

• Endpoint,
• which represents the input and final output,
• Pipeline-shared,
• which is shared in a write-then-read fashion
  within a single pipeline,
• Batch-shared,
• which is comprised of input I/O shared across
  pipelines.

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Application pipelines
Biology
Earth sys.
Physics
Physics
Chemistry
Astrophysics
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I/O amounts of each type I/O
Appl. Endpoint I/O (MB) Endpoint I/O (MB) Pipeline I/O (MB) Pipeline I/O (MB) Batch I/O (MB) Batch I/O (MB)
Appl. Files Traffic Files Traffic Files Traffic
SETI 2 0.34 12 75.43 0 0
BLASTP 2 0.12 0 0 9 329.99
IBIS 20 179.92 99 148.27 17 7.89
CMS 6 63.56 2 12.99 9 3729.67
HF 3 1.96 7 4654.34 1 0
NAUTILUS 124 14.06 369 785.37 8 3.24
AMANDA 6 5.22 11 264.31 29 508.52
It is not mentioned that how much time is used
for I/O.
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Amdahls ratios
App CPU/IO (MIPS/MBPS) MEM/CPU (MB/MIPS) CPU/IO (instr/op)
SETI 45888 0.15 8737 K
BLASTP 37 26.77 144 K
IBIS 34530 0.20 109823 K
CMS 190 2.09 396 K
HF 74 0.16 353 K
NAUTILUS 2287 1.20 8238 K
AMANDA 785 3.77 551 K
I/O traffic is heavy for some applications.
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Scalability is limited by the I/O bandwidth
Storage center
Commodity disk
Why the bandwidth milestones is the storage
device other than the network bandwidth or the
RAM access bandwidth?
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Conclusions

• Shared I/O is the dominant component of all I/O
  traffic, and it causes the serious scalability
  problem for applications.
• Efforts have to be made to eliminate shared I/O
• New file system are required to minimize the I/O

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How to optimize the I/O traffic?

• Minimize the I/O traffic
• Application design (Sequential I/O vs. random
  I/O, Replication)
• Speed up endpoint I/O
• File system (Caching, Database, Ramdisk)

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Another question

• Why the CPU and the Memory are not the bottleneck
  for the system scalability.