/jxperf

Primary LanguageC++MIT LicenseMIT

JXPerf

Java inefficiency detection tool based on CPU performance monitoring counters and hardware debug registers. The tool detects dead writes, silent stores, redundant loads, and memory bloat.

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Contents

Installation

Linux

1. Installation Prerequisites

  • Install Oracle/OpenJDK and Apache Maven.
  • cp set_env.template set_env
  • Modify set_env to make JXPerf_HOME, JAVA_HOME and MAVEN_HOME point to your JXPerf, Java and Maven home.
  • source set_env

2. Installation

$ make

3. Uninstallation

$ make clean

Usage

Linux

1. To run dead store detection

  • Start Profiler
$ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -agentpath:$JXPerf_HOME/build/libagent.so=DeadStore::MEM_UOPS_RETIRED:ALL_STORES:precise=2@<sampling rate> -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py

2. To run silent store detection

  • Start Profiler
$ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -agentpath:$JXPerf_HOME/build/libagent.so=SilentStore::MEM_UOPS_RETIRED:ALL_STORES:precise=2@<sampling rate> -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py

3. To run silent load detection

  • Start Profiler
$ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -agentpath:$JXPerf_HOME/build/libagent.so=SilentLoad::MEM_UOPS_RETIRED:ALL_LOADS:precise=2@<sampling rate> -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py

4. To run data centric analysis

  • Start Profiler
$ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -javaagent:$JAVA_AGENT -agentpath:$JXPerf_HOME/build/libagent.so=DataCentric::MEM_LOAD_UOPS_RETIRED:L1_MISS:precise=2@<sampling rate> -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py
  • The "agent_data" includes two metrics: "Allocation Times" and "L1 Cache Misses"

    • The metric "Allocation Times" reports allocation times for every object, which is represented with the object allocation site

    • The metric "L1 Cache Misses" reports a pair of calling context (i.e., <allocation site, access site>) for every object incurring L1 cache misses

    • To analyze memory bloat

      • Identify the objects suffering from high L1 cache misses by looking into the metric "L1 Cache Misses"
      • Check whether these objects have high allocation times by looking into the metric "Allocation Times"
      • The objects having both high L1 cache misses and allocation times are primary optimization candidates

5. To run NUMA locality analysis

  • Start Profiler
$ $ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -javaagent:$JAVA_AGENT -agentpath:$JXPerf_HOME/build/libagent.so=Numa::MEM_LOAD_UOPS_RETIRED:L1_MISS:precise=2@<sampling rate> -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py
  • The "agent_data" includes:
    • "Fraction of Mismatch": mismatch times of one object over the total mismatch times of whole program
    • "Match Times" and "Mismatch Times": the match and mismatch times of one object
    • "Match Percentage": Match Times / (Match Times + Mismatch Times)
    • "Mismatch Percentage": Mismatch Times / (Match Times + Mismatch Times)

6. To run with generic PMU events

  • Start Profiler
$ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -agentpath:$JXPerf_HOME/build/libagent.so=Generic::PMU_Events:precise=2@<sampling rate> -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py

7. To run heap profiling

  • Start Profiler
$ LD_PRELOAD=$JXPerf_HOME/build/libpreload.so java -agentpath:$JXPerf_HOME/build/libagent.so=Heap -cp <classpath> <java program>
  • Generate profiling results "agent-data"
$ python $JXPerf_HOME/script/process_raw_data.py

8. Attach to a running JVM

  • Open run_attach.sh and change MODE to one of below modes:
    • DataCentric::MEM_LOAD_UOPS_RETIRED:L1_MISS:precise=2@sampling_rate
    • DeadStore::MEM_UOPS_RETIRED:ALL_STORES:precise=2@sampling_rate
    • SilentStore::MEM_UOPS_RETIRED:ALL_STORES:precise=2@sampling_rate
    • SilentLoad::MEM_UOPS_RETIRED:ALL_LOADS:precise=2@sampling_rate
  • Start Profiler
$ ./run_attach.sh <running time in seconds> <pid>

Support Platforms

We tested our tool on following platforms.

Linux

CPU Systems Kernel Architecture
Intel(R) Xeon(R) CPU E5-2650 v4 Ubuntu 14.04.6 Linux 5.1.0 x86_64
Intel(R) Xeon(R) CPU E5-2699 v3 Ubuntu 18.04.3 Linux 5.4.6 x86_64
Intel(R) Xeon(R) CPU E7-4830 v4 CentOS Linux 7 Linux 3.10.0 x86_64

Support JDK Versions

JDK

JDK Versions
JDK 11 & later
OpenJDK 11 & later

License

JXPerf is released under the MIT License.