Intel® VTune™ Profiler

User Guide

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ID 766319
Date 10/31/2024
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Document Table of Contents
Document Table of Contents x
User Guide
User Guide x
Introduction Install Intel® VTune™ Profiler Open Intel® VTune™ Profiler Set Up Project Set Up Analysis Target Analyze Performance Intel® VTune™ Profiler Command Line Interface API Support Troubleshooting Reference Notices and Disclaimers
Introduction x
Tuning Methodology Tutorials and Samples Notational Conventions Get Help Product Website and Support Related Information
Install Intel® VTune™ Profiler x
Sampling Drivers Set Up System for GPU Analysis Verify Intel® VTune™ Profiler Installation Install VTune Profiler Server Security Best Practices
Set Up System for GPU Analysis x
Rebuild and Install the Kernel for GPU Analysis Rebuild and Install Module i915 for GPU Analysis on CentOS* Rebuild and Install Module i915 for GPU Analysis on Ubuntu*
Install VTune Profiler Server x
Set Up Transport Security Configure User Authentication/Authorization
Open Intel® VTune™ Profiler x
Get Started with Intel® VTune™ Profiler Intel® VTune™ Profiler Graphical User Interface Web Server Interface Microsoft Visual Studio* Integration Eclipse* and Intel System Studio IDE Integration Containerization Support
Containerization Support x
Run VTune Profiler in a Container Profile Container Targets from the Host
Set Up Project x
WHERE: Analysis System WHAT: Analysis Target HOW: Analysis Types Search Directories
WHERE: Analysis System x
Analysis System Options
WHAT: Analysis Target x
Analysis Target Options
Search Directories x
Search Order
Set Up Analysis Target x
Prepare Application for Analysis Windows* Targets Linux* Targets Embedded Linux* Targets FreeBSD* Targets QNX* Targets Managed Code Targets Android* Targets Intel® Xeon Phi™ Processor Targets Targets in Virtualized Environments Targets in a Cloud Environment Arbitrary Targets Embedded System Targets
Windows* Targets x
Install the Sampling Drivers for Windows* Targets Debug Information for Windows* Application Binaries Compiler Switches for Performance Analysis on Windows* Targets Debug Information for Windows* System Libraries Add Administrative Privileges
Linux* Targets x
Build and Install the Sampling Drivers for Linux* Targets Debug Information for Linux* Application Binaries Compiler Switches for Performance Analysis on Linux* Targets Enable Linux* Kernel Analysis Resolution of Symbol Names for Linux-Loadable Kernel Modules Analyze Statically Linked Binaries on Linux* Targets Set Up Remote Linux* Target
Set Up Remote Linux* Target x
Set Up Linux* System for Remote Analysis Configure SSH Access for Remote Collection Search Directories for Remote Linux* Targets Temporary Directory for Performance Results on Linux* Targets
Embedded Linux* Targets x
Configure Yocto Project* and VTune Profiler with the Integration Layer Configure Yocto Project*/Wind River* Linux* and Intel® VTune™ Profiler with the Intel System Studio Integration Layer Configure Yocto Project* and Intel® VTune™ Profiler with the Linux* Target Package
FreeBSD* Targets x
Set Up FreeBSD* System
Managed Code Targets x
.NET* Targets Windows Store Application Targets Go* Application Targets
Android* Targets x
Build and Install Sampling Drivers for Android* Targets Set Up Android* System Enable Java* Analysis on Android* System Prepare an Android* Application for Analysis Analyze Unplugged Devices Search Directories for Android* Targets
Targets in Virtualized Environments x
Profile Targets on a VMware* Guest System Profile Targets on a Parallels* Guest System Profile Targets on a KVM* Guest System Profile Targets on a Xen* Virtualization Platform Profile Targets in the Hyper-V* Environment
Profile Targets on a KVM* Guest System x
Profile KVM Kernel Modules from the Host Profile KVM Kernel and User Space on the KVM System Profile KVM Kernel and User Space from the Host
Analyze Performance x
User-Mode Sampling and Tracing Collection Hardware Event-based Sampling Collection Performance Snapshot Algorithm Group Microarchitecture Analysis Group Parallelism Analysis Group Input and Output Analysis Accelerators Analysis Group Platform Analysis Group Platform Analysis Hybrid CPU Analysis Source Code Analysis Custom Analysis Energy Analysis Code Profiling Scenarios Control Data Collection Manage Data Views Manage Result Files
Hardware Event-based Sampling Collection x
Allow Multiple Runs or Multiplex Events Hardware Event-based Sampling Collection with Stacks
Algorithm Group x
Hotspots Analysis for CPU Usage Issues Anomaly Detection Analysis (preview) Memory Consumption Analysis
Hotspots Analysis for CPU Usage Issues x
Hotspots View
Anomaly Detection Analysis (preview) x
Anomaly Detection View
Memory Consumption Analysis x
Memory Consumption and Allocations View
Microarchitecture Analysis Group x
Microarchitecture Exploration Analysis for Hardware Issues Memory Access Analysis for Cache Misses and High Bandwidth Issues
Microarchitecture Exploration Analysis for Hardware Issues x
Microarchitecture Exploration View Microarchitecture Pipe
Memory Access Analysis for Cache Misses and High Bandwidth Issues x
Memory Usage View
Parallelism Analysis Group x
Threading Analysis HPC Performance Characterization Analysis
Threading Analysis x
Threading Efficiency View
HPC Performance Characterization Analysis x
HPC Performance Characterization View
Input and Output Analysis x
Analyze Platform Performance Analyze DPDK Applications Analyze SPDK Applications Analyze Linux Kernel I/O
Accelerators Analysis Group x
GPU Offload Analysis GPU Compute/Media Hotspots Analysis (Preview) CPU/FPGA Interaction Analysis NPU Exploration Analysis
GPU Compute/Media Hotspots Analysis (Preview) x
GPU Compute/Media Hotspots View
CPU/FPGA Interaction Analysis x
CPU/FPGA Interaction View
NPU Exploration Analysis x
NPU Exploration View
Platform Analysis Group x
System Overview Analysis
System Overview Analysis x
Analyze Interrupts Analyze Latency Issues
Custom Analysis x
Custom Analysis Options
Custom Analysis Options x
Hardware Event List Linux* and Android* Kernel Analysis Sampling Interval Sample After Value
Hardware Event List x
Hardware Event Skid Instructions Retired Event Precise Events
Energy Analysis x
Run Energy Analysis View Energy Analysis Data with Intel® VTune™ Profiler Interpret Energy Analysis Data with Intel® VTune™ Profiler
Code Profiling Scenarios x
Java* Code Analysis Configuring Java Data Collection Identifying Hottest Methods Analyzing Stacks for Mixed Code Analyzing Hardware Metrics Limitations See Also Python* Code Analysis Intel® Threading Building Blocks Code Analysis MPI Code Analysis OpenSHMEM* Code Analysis with Fabric Profiler GPU Application Analysis on Intel® HD Graphics and Intel® Iris® Graphics Frame Data Analysis Task Analysis
GPU Application Analysis on Intel® HD Graphics and Intel® Iris® Graphics x
GPU OpenCL™ Application Analysis Intel® Media SDK Program Analysis
Control Data Collection x
Finalization Pause Data Collection Limit Data Collection Generate Command Line Configuration from GUI Minimize Collection Overhead Import External Data
Import External Data x
Use a Custom Collector Create a CSV File with External Data Import Linux Perf* Trace with VTune Profiler Metrics Examples of CSV Format and Imported Data
Manage Data Views x
Switch Viewpoints Control Window Synchronization View Stacks Manage Grid Views Manage Timeline View Change Threshold Values Choose Data Format Group and Filter Data View Data on Inline Functions Analyze Loops Stitch Stacks for Intel® oneAPI Threading Building Blocks or OpenMP* Analysis Search for Data
View Stacks x
Call Stack Mode Metrics Distribution Over Call Stacks
Manage Result Files x
VTune Profiler Filenames and Locations Import Results and Traces into VTune Profiler GUI Compare Results
Compare Results x
Compare Source Code View Comparison Data
View Comparison Data x
Comparison Summary Bottom-up Comparison Top-down Tree Comparison
Intel® VTune™ Profiler Command Line Interface x
vtune Command Syntax vtune Actions Run Command Line Analysis Work with Results from Command Line Generate Command Line Reports Command Line Usage Scenarios Command Line Interface Reference Report Problems from Command Line
Run Command Line Analysis x
performance-snapshot Command Line Analysis hotspots Command Line Analysis anomaly-detection Command Line Analysis threading Command Line Analysis memory-consumption Command Line Analysis hpc-performance Command Line Analysis uarch-exploration Command Line Analysis memory-access Command Line Analysis tsx-exploration Command Line Analysis tsx-hotspots Command Line Analysis sgx-hotspots Command Line Analysis gpu-hotspots Command Line Analysis gpu-offload Command Line Analysis npu graphics-rendering Command Line Analysis fpga-interaction Command Line Analysis io Command Line Analysis system-overview Command Line Analysis runsa/runss Custom Command Line Analysis Configure Analysis Options from Command Line
Configure Analysis Options from Command Line x
Collect System-Wide Data from Command Line Collect Data on Remote Linux* Systems from Command Line Configure GPU Analysis from Command Line Specify Search Directories from Command Line Specify Result Directory from Command Line Pause Collection from Command Line Manage Analysis Duration from Command Line Limit Data Collection from Command Line
Work with Results from Command Line x
View Command Line Results in the GUI Import Results from Command Line Re-finalize Results from Command Line
Generate Command Line Reports x
Summary Report Hotspots Report Hardware Events Report Callstacks Report Timeline Report Top-down Report GPU Compute/Media Hotspots Report gprof-cc Report Difference Report View Source Objects from Command Line Save and Format Command Line Reports Filter and Group Command Line Reports
Command Line Usage Scenarios x
Use VTune Profiler Server in Containers Android* Target Analysis from the Command Line OpenMP* Analysis from the Command Line Java* Code Analysis from the Command Line
Command Line Interface Reference x
Option Descriptions and General Rules allow-multiple-runs analyze-kvm-guest analyze-system app-working-dir archive call-stack-mode collect collect-with column command cpu-mask csv-delimiter cumulative-threshold-percent custom-collector data-limit discard-raw-data duration filter finalization-mode finalize format group-by help import inline-mode knob kvm-guest-kallsyms kvm-guest-modules limit loop-mode mrte-mode no-follow-child no-summary no-unplugged-mode quiet report report-knob report-output report-width result-dir resume-after return-app-exitcode ring-buffer search-dir show-as sort-asc sort-desc source-object source-search-dir stack-size start-paused strategy target-install-dir target-system target-tmp-dir target-duration-type target-pid target-process time-filter trace-mpi user-data-dir verbose version
API Support x
Support for Instrumentation and Tracing Technology API (ITT API) JIT Profiling API System APIs Supported by Intel® VTune™ Profiler
Support for Instrumentation and Tracing Technology API (ITT API) x
Basic Usage and Configuration Instrumentation and Tracing Technology API Reference
Basic Usage and Configuration x
Configure Your Build System Attach ITT APIs to a Launched Application Instrument Your Application Minimize ITT API Overhead View Instrumentation and Tracing Technology (ITT) API Task Data in Intel® VTune™ Profiler
Instrumentation and Tracing Technology API Reference x
Domain API String Handle API Collection Control API Thread Naming API Task API Frame API Histogram API User-Defined Synchronization API Event API Counter API Context Metadata API Load Module API Memory Allocation APIs
JIT Profiling API x
Using JIT Profiling API JIT Profiling API Reference
JIT Profiling API Reference x
iJIT_NotifyEvent iJIT_IsProfilingActive iJIT_ GetNewMethodID
Troubleshooting x
Best Practices: Resolve Intel® VTune™ Profiler BSODs, Crashes, and Hangs in Windows* OS Error Message: Application Sets Its Own Handler for Signal Error Message: Cannot Enable Event-Based Sampling Collection Error Message: Cannot Collect GPU Hardware Metrics Error Message: Cannot Load Data File Error Message: Cannot Locate Debugging Information Error Message: Cannot Open Data Error Message: Client Is Not Authorized to Connect to Server Error Message: Root Privileges Required for Processor Graphics Events Error Message: No Pre-built Driver Exists for This System Error Message: Not All OpenCL™ API Profiling Callbacks Are Received Error Message: Problem Accessing the Sampling Driver Error Message: Required Key Not Available Error Message: Scope of ptrace System Call Is Limited Error Message: Stack Size Is Too Small Error Message: Symbol File Is Not Found Problem: Analysis of the .NET* Application Fails Problem: Cannot Access VTune Profiler Documentation Problem: CPU time for Hotspots or Threading Analysis is Too Low Problem: 'Events= Sample After Value (SAV) * Samples' Is Not True If Multiple Runs Are Disabled Problem: Guessed Stack Frames Problem: GUI Hangs or Crashes Problem: Inaccurate Sum in the Grid Problem: Information Collected via ITT API Is Not Available When Attaching to a Process Problem: No GPU Utilization Data Is Collected Problem: Same Functions Are Compared As Different Instances Problem: Skipped Stack Frames Problem: Stack in the Top-Down Tree Window Is Incorrect Problem: Stacks in Call Stack and Bottom-Up Panes Are Different Problem: System Functions Appear in the User Functions Only Mode Problem: Intel® VTune™ Profiler is Slow to Respond When Collecting or Displaying Data Problem: Intel® VTune™ Profiler is Slow on X-Servers with SSH Connection Problem: Unexpected Paused Time Problem: {Unknown Timer} in the Platform Power Analysis Viewpoint Problem: Unknown Critical Error Due to Disabled Loopback Interface Problem: Unknown Frames Problem: Unsupported Microsoft* Windows* OS
Reference x
User Interface Reference CPU Metrics Reference GPU Metrics Reference OpenCL™ Kernel Analysis Metrics Reference Energy Analysis Metrics Reference Intel Processor Events Reference
User Interface Reference x
Context Menu: Grid Context Menus: Call Stack Pane Context Menus: Project Navigator Context Menus: Source/Assembly Window Dialog Box: Binary/Symbol Search Dialog Box: Source Search Hot Keys Menu: Customize Grouping Menu: Intel VTune Profiler Pane: Call Stack Pane: Options - General Pane: Options - Result Location Pane: Options - Source/Assembly Project Navigator Pane: Timeline Toolbar: Configure Analysis Toolbar: Filter Toolbar: Source/Assembly Toolbar: Intel VTune Profiler Window: Bandwidth - Platform Power Analysis Window: Bottom-up Window: Caller/Callee Window: Cannot Find <file type> File Window: Collection Log Window: Compare Results Window: Configure Analysis Window: Core Wake-ups - Platform Power Analysis Window: Correlate Metrics - Platform Power Analysis Window: CPU C/P States - Platform Power Analysis Window: Debug Window: Event Count - Hardware Events Window: Flame Graph Window: Graphics - GPU Compute/Media Hotspots Window: Graphics C/P States - Platform Power Analysis Window: NC Device States - Platform Power Analysis Window: Platform Window: Platform Power Analysis Window: Sample Count - Hardware Events Window: SC Device States - Platform Power Analysis Window: Summary Window: System Sleep States - Platform Power Analysis Window: Temperature/Thermal Sample - Platform Power Analysis Window: Timer Resolution - Platform Power Analysis Window: Top-down Tree Window: Uncore Event Count - Hardware Events Window: Wakelocks - Platform Power Analysis
Window: Summary x
Window: Summary - Input and Output Summary Window: Summary - Microarchitecture Exploration Window: Summary - GPU Analysis Window: Summary - Hardware Events Window: Summary - Hotspots by CPU Utilization Window: Summary - HPC Performance Characterization Window: Summary - Memory Consumption Window: Summary - Memory Usage Window: Summary - Platform Power Analysis
GPU Metrics Reference x
ALU0 Active ALU0 Instructions ALU1 Active ALU1 Instructions ALU2 Active ALU2 Instructions ALU0 and ALU1 Active ALU0 and ALU2 Active ALU0 and XMX Utilization Average Time Computing Threads Started Computing Threads Started, Threads/sec CPU Time EU 2 FPU Pipelines Active EU Array Active EU Array Idle EU Array Stalled/Idle EU Array Stalled EU IPC Rate EU Send pipeline active EU Threads Occupancy Global GPU EU Array Usage GPU Instruction Cache L3 Miss Ratio GPU L3 Atomics GPU L3 Bound GPU L3 Miss Ratio GPU L3 Misses GPU L3 Misses, Misses/sec GPU Load Store Cache Miss Ratio GPU Load Store Cache L3 Miss Ratio GPU LSC Atomics GPU LSC Fences GPU Media Read Requests GPU Media Write Requests GPU SLM Atomics GPU SLM Fences GPU Memory Read Bandwidth, GB/sec GPU Memory Texture Read Bandwidth, GB/sec GPU Memory Write Bandwidth, GB/sec GPU Sampler L3 Miss Ratio GPU Texel Quads Count, Count/sec GPU Utilization Graphics Security Controller Busy Host to GPU Memory Read Bandwidth Host-to-GPU Memory Write Bandwidth Instance Count Instruction Cache Miss Ratio L3 Busy L3 Input Available L3 Instruction Cache Bandwidth L3 Load Store Cache Read Bandwidth L3 Load Store Cache Write Bandwidth L3 Miss Ratio L3 Output Ready L3 Read Bandwidth L3 SQ Full L3 Stalled L3 Write Bandwidth L3 Sampler Bandwidth, GB/sec L3 Shader Bandwidth, GB/sec LLC Miss Rate due GPU Lookups LLC Miss Ratio due GPU Lookups LSC Input Available LSC Output Ready LSC Partial Writes Local Maximum GPU Utilization Multiple Pipe Utilization Occupancy PS EU Active % PS EU Stall % Ratio to Max Bandwidth, % Ratio to Max Bandwidth, % Ratio to Max Bandwidth, % Render/GPGPU Command Streamer Loaded Sampler Input Available Sampler Output Ready Samples Blended Samples Killed in PS, pixels Samples Written Sampler Busy Sampler Is Bottleneck Shared Local Memory Read Bandwidth, GB/sec Shared Local Memory Write Bandwidth, GB/sec SIMD Width SLM Bank Conflicts Stack-to-stack Incoming Bandwidth Stack-to-stack Outgoing Bandwidth System Memory Read Bandwidth System Memory Write Bandwidth Size Total, GB/sec Thread Dispatcher Active TLB Misses Total Time Typed Memory Read Bandwidth, GB/sec Typed Memory Write Bandwidth, GB/sec Typed Reads Coalescence Typed Writes Coalescence Untyped Memory Read Bandwidth, GB/sec Untyped Memory Write Bandwidth, GB/sec Untyped Reads Coalescence Untyped Writes Coalescence Video Codec Busy Video Codec Read Requests Video Codec Write Requests Video Codec 2 Busy Video Codec 2 Read Requests Video Codec 2 Write Requests Video Enhancement Busy Video Enhancement Read Requests Video Enhancement Write Requests Video Enhancement 2 Busy Video Enhancement 2 Read Requests Video Enhancement 2 Write Requests VS EU Active VS EU Stall XVE Barrier Stall XVE Bit Manipulation Instructions XVE Control Stall XVE Dist or Acc Stall XVE INT16\INT32\INT64\FP16\FP32\FP64 Instructions XVE FP16\BF16\INT8\INT4\INT2 XMX Instructions XVE Instruction Fetch Stall XVE Pipe Stall XVE Send Stall XVE SBID Stall XVE XMX Instructions XVE XMX Pipeline Active
OpenCL™ Kernel Analysis Metrics Reference x
Computing Task Total Time Instance Count SIMD Width SIMD Utilization Work Size
Energy Analysis Metrics Reference x
Available Core Time C-State D0ix States DRAM Self Refresh Energy Consumed (mJ) Idle Wake-ups P-State S0ix States Temperature Timer Resolution Total Time in C0 State Total Time in Non-C0 States Total Time in S0 State Total Wake-up Count Wake-ups Wake-ups/sec per Core
User Guide

Java* Code Analysis

Use the Intel® VTune™ Profiler to analyze Java* applications executed with Oracle* or OpenJDK* (Linux* only).

Even though Java code execution is handled with a Managed Runtime Environment, it can be as ineffective in terms of data management as in programs written using native languages. For example, if you are conscious about performance of your data mining Java application, you need to take into consideration your target platform memory architecture, cache hierarchy and latency of access to memory levels. From the platform microarchitecture point of view, profiling of Java applications is similar to profiling of native applications but with one major difference: to see performance metrics against their program source code, the profiling tool must be able to map metrics of the binary code either compiled or interpreted by the JVM back to the original source code in Java or C/C++.

VTune Profiler provides a low-overhead analysis of the JIT compiled code that is available for both user-mode sampling and tracing and hardware event-based sampling analysis types. The analysis of the interpreted Java methods is limited.

To enable the Java code analysis with the Intel® VTune™ Profiler and interpret data:

Configuring Java Data Collection

To configure your performance analysis for Java code, you may use either GUI or command line (vtune) configuration. You may run Java code analysis using one of the following modes:

To configure Java analysis in the Launch Application mode:

  1. Embed your java command in a batch file or executable script.

    For example, create a run.bat file on Windows* or run.sh file on Linux* with the following command:

    Windows: 

    > java.exe -Xcomp -Djava.library.path=native_lib\ia32 -cp C:\Design\Java\mixed_stacks MixedStacksTest 3 2

    Linux: 

    $ java -Xcomp -Djava.library.path=native_lib/ia32 -cp /home/Design/Java/mixed_stacks MixedStacksTest 3 2

  2. Create a project.

  3. In the Configure Analysis window > WHERE pane, specify your analysis system, for example, Local Host.

  4. In the WHAT pane, choose the Application to Launch target type.

  5. In the Application field, specify a path to this run file . For example, on Linux:

  6. In the Advanced section, select the Auto Managed code profiling mode and enable the Analyze child processes option.

Similarly, you can configure an analysis with the VTune Profiler command line interface, vtune. For example, for the Hotspots analysis on Linux run the following command line: 

$ vtune -collect hotspots -- run.sh

or directly: 

$ vtune -collect hotspots -- java -Xcomp -Djava.library.path=native_lib/ia32 -cp home/Design/Java/mixed_stacks MixedStacksTest 3 2

To configure Java analysis in the Attach to Process mode:

In case your Java application needs to run for some time or cannot be launched at the start of this analysis, you may attach the VTune Profiler to the standalone Java process. On Linux, you can also attach the VTune Profiler to a C/C++ application with an embedded JVM instance for hardware event-based sampling analysis types. To do this, select the Attach to Process target type in the WHAT pane and specify the java process name or PID.

You may use the command line interface to attach the analysis to the Java process. For example, the following command attaches the Hotspots analysis to the Java process: 

$ vtune -collect hotspots -target-process java

The following command line example attaches the Hotspots analysis to the Java process by its PID: 

$ vtune -collect hotspots -target-pid 1234

NOTE:
The dynamic attach mechanism is supported only with the Java Development Kit (JDK).

To configure Java analysis in the Attach to Process mode under Low-privilege Account (Linux* Only):

For hardware event-based sampling analysis types, you can attach the VTune Profiler running under the superuser account to a Java process or a C/C++ application with embedded JVM instance running under a low-privileged user account. For example, you may attach the VTune Profiler to Java based daemons or services.

To do this, run the VTune Profiler under the root account, select the Attach to Process target type and specify the java process name or PID.

Identifying Hottest Methods

You may run the Hotspot analysis to get a list of the hottest methods along with their timing metrics and call stacks. The workload distribution over threads is also displayed in the Timeline pane. Thread naming helps to identify where exactly the most resource consuming code was executed. For example, on Linux*:

Analyzing Stacks for Mixed Code

If you are pursuing maximum performance on a platform, consider writing and compiling performance critical modules of your Java project in native languages like C or even assembly. This way of programming helps to employ powerful CPU resources like vector computing (implemented via SIMD units and instruction sets). In this case, compute-intensive functions become hotspots in the profiling results, which is expected as they do most of the job. However, you might be interested not only in hotspot functions, but in identifying locations in Java code these functions were called from via a JNI interface. Tracing such cross-runtime calls in the mixed language algorithm implementations could be a challenge.

To analyze mixed code profiling results, the VTune Profiler is "stitching" the Java call stack with the subsequent native call stack of C/C++ functions. The reverse call stacks stitching works as well. For example, on Windows*:

Native function

Mixed native/Java call stack

Native module

Compiled methods in the Java call stack

NOTE:

Due to inlining during the compilation stage, some functions may not appear in the stack by default. Make sure to select the Show inline functions option for the Inline Mode on the filter bar.

Analyzing Hardware Metrics

VTune Profiler also provides an advanced profiling option of optimizing Java applications for the CPU microarchitecture utilized in your platform. Although Java and JVM technology is intended to free a developer from hardware architecture specific coding, once Java code is optimized for the current Intel microarchitecture, it will most probably keep this advantage for future generations of CPUs. You may use the hardware event-based sampling data collection that monitors hardware events in the CPU's pipeline and can identify coding pitfalls limiting the most effective execution of instructions in the CPU. The CPU metrics are available and can be displayed against the application modules, functions, and Java code source lines. You may also run the hardware event-based sampling collection with stacks when you need to find out a call path for a function called in a driver or middleware layer in your system.

Limitations

VTune Profiler supports analysis of Java applications with some limitations:

  • System-wide profiling is not supported for managed code.

  • The JVM interprets some rarely called methods instead of compiling them for the sake of performance. VTune Profiler does not recognize interpreted Java methods and marks such calls as !Interpreter in the restored call stack.

    If you want such functions to be displayed in stacks with their names, force the JVM to compile them by using the -Xcomp option (show up as [Compiled Java code] methods in the results). However, the timing characteristics may change noticeably if many small or rarely used functions are being called during execution.

  • When opening source code for a hotspot, the VTune Profiler may attribute events or time statistics to an incorrect piece of the code. It happens due to JDK Java VM specifics. For a loop, the performance metric may slip upward. Often the information is attributed to the first line of the hot method's source code. In the example below, a real hotspot line consuming most CPU time is line 35.

  • Consider events and time mapping to the source code lines as approximate.

  • For the Hotspots analysis type in the user-mode sampling mode, the VTune Profiler may display only a part of the call stack. To view the complete stack on Windows, use the -Xcomp additional command line JDK Java VM option that enables the JIT compilation for better quality of stack walking.

    To view the complete stack on Linux, use additional command line JDK Java VM options that change behavior of the Java VM:

    • Use the -Xcomp additional command line JDK Java VM option that enables the JIT compilation for better quality of stack walking.

    • On Linux* x86, use client JDK Java VM instead of the server Java VM: either explicitly specify -client, or simply do not specify -server JDK Java VM command line option.

    • On Linux x64, specify -XX:-UseLoopCounter command line option that switches off on-the-fly substitution of the interpreted method with the compiled version.

  • Java application profiling is supported for the Hotspots and Microarchitecture analysis types. Support for the Threading analysis is limited as some embedded Java synchronization primitives (which do not call operating system synchronization objects) cannot be recognized by the VTune Profiler. As a result, some of the timing metrics may be distorted.

  • There are no dedicated libraries supplying a user API for collection control in the Java source code. However, you may want to try applying the native API by wrapping the __itt calls with JNI calls.

Parent topic: Code Profiling Scenarios
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