Comparison of JVM Phases on Data Cache Performance

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Comparison of JVM Phases on Data Cache
Performance

• Shiwen Hu and Lizy K. John
• Laboratory for Computer Architecture
• The University of Texas at Austin

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Motivation

• Execution of Java programs consists of distinct
  JVM phases
• JIT compilation
• Garbage collection
• Execution
• Efficient execution of Java programs necessitates
  a comparative study of requirements and
  characteristics of JVM phases

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Outline

• Experimental methodology
• Varying cache metrics
• Cache size, set associativity, block size
• Decomposition by miss types
• Time varying cache behavior
• Conclusion

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Methodology

• LaTTe JVM
• An open-source, state-of-the-art JVM
• Memory management of LaTTe JIT compiler
• Reusable initial stack 50KB
• Allocate dynamic stacks when necessary
  recyclable
• Heap Management
• Large object area indexed by a hash table
• Small object area heads indicating object sizes

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Methodology (Cont.)

• Experimental workloads SPECjvm 98 benchmarks
• Using s10 data set
• Cache simulator
• Based on Cachesim5 from Suns Shade V6 tool suite
• A JVM phase aware cache simulator
• Default configuration
• 64KB, 32B blocks, 4-way set associative

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Breakdown of JVM phases

• JIT compilation and execution phases dominate
• In terms of instruction counts, data references,
  and data misses
• Garbage collector has the highest miss rates
• Large working set (heap) and pointer-chasings
• But, rarely affects overall cache performance

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Breakdown of JVM phases (Cont.)
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Varying cache size

• Increasing cache size is more effective on JIT
  compilation than on garbage collection
• Larger working set of garbage collector
• Pointer chasing access pattern of garbage
  collector
• Stacks of most JIT compilations can be held in
  128K cache
• Varying effect on execution phase
• More effective on mpegaudio than on db

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Varying cache size (Cont.)
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Varying set associativity

• Increasing set associativity rarely affects JIT
  compilation and garbage collection
• Negligible conflict misses due to uniform
  accesses to heap or stacks
• Dominated by capacity misses
• Short lives of JIT objects
• Varying effectiveness on execution phase
• mtrt 52 misses eliminated
• db and javac 13 misses eliminated

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Varying set associativity (Cont.)
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Varying block size

• Effective on JIT compilation and garbage
  collection
• JIT compilation good spatial locality due to
  stack initialization
• Garbage collection good spatial locality during
  sweep phase
• Varying effectiveness on execution phase
• Larger block db, jess, mpegaudio, and mtrt
• Smaller block compress, jack, javac

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Varying block size (Cont.)
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Decomposition by miss types - JIT

• Capacity misses dominate
• Less compulsory misses
• Reusable initial stack
• Overlapped dynamic
• stacks
• Negligible conflict misses
• Splitting cache rarely
• affects miss type
• composition

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Decomposition by miss types - GC

• Fewest compulsory misses in unified cache
• Cache blocks accessed during execution phase
• More compulsory misses
• in split cache
• Uniform heap sweeping

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Decomposition by miss types - EXEC

• Relatively more compulsory misses
• Heap objects allocation and initialization
• Variety reveals program
• characteristics
• Splitting cache rarely
• affects miss type
• composition

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Time varying behavior

• Importance of separating JVM activities from
  application activities
• Java programs execute on JVMs, differing with
  C/C programs
• Correlating performance results with JVM or
  application characteristics is important to
  design better JVMs

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Time varying behavior (Cont.)

• JVM specific operations dominate the startup and
  end of application execution
• Class loadings, method compilations
• Few garbage collections
• Corresponding to burst of cache misses
• Four passes of JIT compilation correspond to four
  bursts of cache misses

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Time varying behavior - compress

• Less GC and JIT activities
• Cyclic behavior
• Two phases during execution

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Time varying behavior - mtrt

• More GC and JIT activities
• No cyclic behavior

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Time varying behavior - startup

• Identical behavior during startup
• First 110 million instructions
• Sharing of harness classes among SPECjvm 98
  benchmarks prolongs the duration

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Conclusion

• Comparative study of cache performance of
  distinct JVM phases
• Deterministic characteristics of cache behavior
• JIT compilation traversing intermediate data
  structures
• Garbage collection large working set and pointer
  chasings

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Conclusion (Cont.)

• Near identical cache performance of JIT
  compilation among applications
• Varying cache behavior during execution phase
  reveal characteristics of applications

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Thanks