User Guide

Intel® VTune™ Profiler User Guide

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ID 766319
Date 11/07/2023
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Document Table of Contents
Document Table of Contents x
Intel® VTune™ Profiler User Guide
Intel® VTune™ Profiler 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 macOS* 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 (Preview)
GPU Compute/Media Hotspots Analysis (Preview) x
GPU Compute/Media Hotspots View
CPU/FPGA Interaction Analysis x
CPU/FPGA Interaction View
NPU Exploration Analysis (Preview) 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
Highly Accurate CPU Time Data Collection 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 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 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
Instrumentation and Tracing Technology APIs JIT Profiling API System APIs Supported by Intel® VTune™ Profiler
Instrumentation and Tracing Technology APIs 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: VTune Profiler is Slow to Respond When Collecting or Displaying Data Problem: 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: Unreadable Text on macOS* Problem: Unsupported Microsoft* Windows* OS Warnings about Accurate CPU Time Collection
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 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 Host to GPU Memory Read Bandwidth Host-to-GPU Memory Write Bandwidth Global GPU EU Array Usage GPU L3 Bound GPU L3 Miss Ratio GPU L3 Misses GPU L3 Misses, Misses/sec GPU Memory Read Bandwidth, GB/sec GPU Memory Texture Read Bandwidth, GB/sec GPU Memory Write Bandwidth, GB/sec GPU Texel Quads Count, Count/sec GPU Utilization Instance Count L3 Read Bandwidth 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 Local Maximum GPU 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 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 Stack-to-stack Incoming Bandwidth Stack-to-stack Outgoing Bandwidth System Memory Read Bandwidth System Memory Write Bandwidth Size Total, GB/sec 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 VS EU Active VS EU Stall
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
Intel® VTune™ Profiler User Guide

Window: Summary - Hotspots

Use the Summary window as your starting point of the performance analysis with the Intel® VTune™ Profiler. To access this window, click the Summary sub-tab in the result tab.

Depending on the analysis type, the Summary window provides the following application-level statistics in the Hotspots viewpoint:

NOTE:

You may click the Copy to Clipboard button to copy the content of the selected summary section to the clipboard.

Analysis Metrics

The Summary window displays a list of CPU metrics that help you estimate an overall application execution. For a metric description, hover over the corresponding question mark icon to read the pop-up help. For metric values flagged as performance issues, hover over such a value for details:

Use the Elapsed Time metric as your primary indicator and a baseline for comparison of results before and after optimization. Note that for multithreaded applications, the CPU Time is different from the Elapsed Time since the CPU Time is the sum of CPU time for all application threads.

For some analysis types, the Effective CPU Time is classified per CPU utilization as follows:

Utilization Type

Description

Idle

Idle utilization. By default, if the CPU Time is insignificant (less than 50% of 1 CPU), such CPU utilization is classified as idle.

Poor

Poor utilization. By default, poor utilization is when the number of simultaneously running CPUs is less than or equal to 50% of the target CPU utilization.

OK

Acceptable (OK) utilization. By default, OK utilization is when the number of simultaneously running CPUs is between 51-85% of the target CPU utilization.

Ideal

Ideal utilization. By default, Ideal utilization is when the number of simultaneously running CPUs is between 86-100% of the target CPU utilization.

The Overhead and Spin Time metrics, if provided (depend on the analysis), can tell you how your application's use of synchronization and threading libraries is impacting the CPU time. Review the metrics within these categories to learn where your application might be spending additional time making calls to synchronization and threading libraries such as system synchronization API, Intel® oneAPI Threading Building Blocks(oneTBB ), and OpenMP*. VTune Profiler provides the following types of inefficiencies in your code taking CPU time:

Imbalance or Serial Spinning Time

Imbalance or Serial Spinning time is CPU time when working threads are spinning on a synchronization barrier consuming CPU resources. This can be caused by load imbalance, insufficient concurrency for all working threads or waits on a barrier in the case of serialized execution.

Lock Contention Spin Time

Lock Contention time is CPU time when working threads are spinning on a lock consuming CPU resources. High metric value may signal inefficient parallelization with highly contended synchronization objects. To avoid intensive synchronization, consider using reduction, atomic operations or thread local variables where possible.

Other Spin Time

This metric shows unclassified Spin time spent in a threading runtime library.

Creation Overhead Time

Creation time is CPU time that a runtime library spends on organizing parallel work.

Scheduling Overhead Time

Scheduling time is CPU time that a runtime library spends on work assignment for threads. If the time is significant, consider using coarse-grain work chunking.

Reduction Overhead Time

Reduction time is CPU time that a runtime library spends on loop or region reduction operations.

Atomics Overhead Time

Atomics time is CPU time that a runtime library spends on atomic operations.

Other Overhead Time

This metric shows unclassified Overhead time spent in a threading runtime library.

Depending on the analysis type, the VTune Profiler may analyze a metric, compare its value with the threshold value provided by Intel architects, and highlight the metric value in pink as a performance issue for an application as a whole. The issue description for such a value may be provided below the critical metric or when you hover over the highlighted metric.

Each metric in the list shows up as a hyperlink. Clicking a hyperlink opens the Bottom-up window and sorts the grid by the selected metric or highlights the selected object in the grid.

Top Hotspots

VTune Profiler displays the most performance-critical functions and their CPU Time in the Top Hotspots section. Optimizing these functions typically results in improving overall application performance. Clicking a function in the list opens the Bottom-up window with this function selected.

The grayed-out [Others] module, if provided, displays the total value for all other functions in the application that are not included into this table.

NOTE:

You can control the number of objects in this list and displayed metrics via the viewpoint configuration file.

Insights

If you ran the analysis with the default Show additional performance insights option, the Summary view will include the Insights section that provides additional metrics for your target such as efficiency of the hardware usage and vectorization. This information helps you identify potential next steps for your performance analysis and understand where you could focus your optimization efforts.

Top Tasks

This section provides a list of tasks that took most of the time to execute, where tasks are either code regions marked with Task API, or system tasks enabled to monitor Ftrace* events, Atrace* events, Intel Media SDK programs, OpenCL™ kernels, and so on.

Clicking a task type in the table opens the grid view (for example, Bottom-up or Event Count) grouped by the Task Type granularity. See Task Analysis for more information.

Average Bandwidth

This sections shows total memory bandwidth, Read Bandwidth, and Write Bandwidth per package averaged over the whole profiling session. This data is available if you run an analysis type collecting platform-wide metrics, for example, CPU/GPU Concurrency.

The performance of your application may be limited by memory bandwidth if values in this table are close to maximum possible bandwidth on your platform. You can use benchmarks to measure your platform maximum bandwidth, for example: Intel Memory Latency Checker.

CPU Utilization Histogram

Explore the CPU Utilization Histogram to analyze the percentage of the wall time the specific number of CPUs were running simultaneously.

Use This To Do This

Vertical bars

Hover over the bar to identify the amount of Elapsed time the application spent using the specified number of logical CPUs.

Target Utilization

Identify the target CPU utilization. This number is equal to the number of logical CPUs. Consider this number as your optimization goal.

Average CPU Utilization

Identify the average number of CPUs used aggregating the entire run. It is calculated as CPU time / Elapsed time.

CPU utilization at any point in time cannot surpass the available number of logical CPUs. Even when the system is oversubscribed, and there are more threads running than CPUs, the CPU utilization is the same as the number of CPUs.

Use this number as a baseline for your performance measurements. The closer this number to the number of logical CPUs, the better, except for the case when the CPU time goes to spinning.

Utilization Indicator bar

Analyze how the various utilization levels map to the number of simultaneously utilized logical CPUs.

NOTE:

In the CPU Utilization histogram, the VTune Profiler treats the Spin and Overhead time as Idle CPU utilization. Different analysis types may recognize Spin and Overhead time differently depending on availability of call stack information. This may result in a difference of CPU Utilization graphical representation per analysis type.

Frame Rate Histogram

If you used the Frame API to mark the start and finish of the code regions executed repeatedly (frames) in your graphics application, the VTune Profiler analyzes this data and helps you identify regions that ran slowly. Explore the Frame Rate Histogram section and identify slow and fast frame domains.

Use This

To Do This

Domain drop-down menu

Choose a frame domain to analyze with the frame rate histogram. If only one domain is available, the drop-down menu is grayed out. Then, you can switch to the Bottom-up window grouped by Frame Domain, filter the data by slow frames and switch to the Function grouping to identify functions in the slow frame domains. Try to optimize your code to keep the frame rate constant (for example, from 30 to 60 frames per second).

Vertical bars

Hover over a bar to see the total number of frames in your application executed with a specific frame rate. High number of slow or fast frames signals a performance bottleneck.

Frame rate bar

Use the sliders to adjust the frame rate threshold (in frames per second) for the currently open result and all subsequent results in the project.

OpenMP Analysis Collection Time

This section displays the Collection Time as well as metrics for the duration of serial (outside parallel regions) and parallel portions of the program. If the Serial Time is significant, review the Top Serial Hotspots section and consider options to minimize serial execution, either by introducing more parallelism or by doing algorithm or microarchitecture tuning for sections that seem unavoidably serial. For high thread-count machines, serial sections have a severe negative impact on potential scaling (Amdahl's Law) and should be minimized as much as possible.

Top OpenMP Regions by Potential Gain

To estimate the efficiency of CPU utilization in the parallel part of the code, use the Potential Gain metric. This metric estimates the difference in the Elapsed time between the actual measurement and an idealized execution of parallel regions, assuming perfectly balanced threads and zero overhead of the OpenMP runtime on work arrangement. Use this data to understand the maximum time that you may save by improving parallel execution.

The Summary window provides a detailed table listing the top five parallel regions with the highest Potential Gain metric values.

If Potential Gain for a region is significant, you can go deeper and select the link on a region name to navigate to the Bottom-up window employing the /OpenMP Region/OpenMP Barrier-to-Barrier Segment/.. dominant grouping that provides detailed analysis of inefficiency metrics like Imbalance by barriers.

Clicking the process name links leads you to the Bottom-up window grouped by /Process/OpenMP Region/.. where you can get more details on OpenMP inefficiencies for MPI ranks.

Top OpenMP processes by MPI Communication Spin Time

For MPI analysis result including more than one process with OpenMP regions, the Summary window shows a section with top processes laying on a critical path of MPI execution with Serial Time and OpenMP Potential Gain aggregated per process:

OpenMP Region CPU Utilization Histogram

Use This

To Do This

OpenMP Region drop-down menu

Filter the histogram data by the selected OpenMP region. Start your OpenMP analysis from the top of the list that is sorted by the Potential Gain metric value, which is the maximum elapsed time that could be saved if the OpenMP region is optimized to have no load imbalance assuming no runtime overhead (Collection Time minus Ideal Time).

Vertical bars

Hover over a bar to see how much time the specific number of CPUs were running simultaneously in the OpenMP region selected from the OpenMP Region drop-down menu. Spin and Overhead time adds to the Idle CPU utilization value.

Target Concurrency

Identify the target concurrency level. This number is equal to the number of logical CPUs. Consider this number as your optimization goal.

Average

Identify the average number of CPUs used aggregating the entire run. It is calculated as CPU time / Elapsed time.

Use this number as a baseline for your performance measurements. The closer this number to the number of logical CPUs (Target Concurrency), the better, except for the case when the CPU time goes to spinning.

Utilization Indicator bar

Analyze how the various utilization levels map to the number of simultaneously running CPUs.

OpenMP Region Duration Histograms

Use This

To Do This

OpenMP Region drop-down menu

Choose an OpenMP region to see the number of instances distributed by duration.

Instance Count

Hover over a bar to see the total number of OpenMP region instances in your application executed with a specific duration. High number of slow or fast regions signals a performance bottleneck.

Duration Type (sec)

Use the sliders to adjust the duration threshold (in seconds) for the currently open result. Initial distribution of region instances by Fast/Good/Slow categories is done as a ratio of 20/40/20 between min and max region time values.

Collection and Platform Info

This section provides the following data:

Application Command Line

Path to the target application.

Operating System

Operating system used for the collection.

Computer Name

Name of the computer used for the collection.

Result Size

Size of the result collected by the VTune Profiler.

Collection start time

Start time (in UTC format) of the external collection. Explore the Timeline pane to track the performance statistics provided by the custom collector over time.

Collection stop time

Stop time (in UTC format) of the external collection. Explore the Timeline pane to track the performance statistics provided by the custom collector over time.

Collector type

Type of the data collector used for the analysis. The following types are possible:

CPU Information

Name

Name of the processor used for the collection.

Frequency

Frequency of the processor used for the collection.

Logical CPU Count

Logical CPU count for the machine used for the collection.

Physical Core Count

Number of physical cores on the system.

User Name

User launching the data collection. This field is available if you enabled the per-user event-based sampling collection mode during the product installation.

GPU Information

Name

Name of the Graphics installed on the system.

Vendor

GPU vendor.

Driver

Version of the graphics driver installed on the system.

Stepping

Microprocessor version.

EU Count

Number of execution units (EUs) in the Render and GPGPU engine. This data is Intel® HD Graphics and Intel® Iris® Graphics (further: Intel Graphics) specific.

Max EU Thread Count

Maximum number of threads per execution unit. This data is Intel Graphics specific.

Max Core Frequency

Maximum frequency of the Graphics processor. This data is Intel Graphics specific.

Graphics Performance Analysis

GPU metrics collection is enabled on the hardware level. This data is Intel Graphics specific.

NOTE:

Some systems disable collection of extended metrics such as L3 misses, memory accesses, sampler busyness, SLM accesses, and others in the BIOS. On some systems you can set a BIOS option to enable this collection. The presence or absence of the option and its name are BIOS vendor specific. Look for the Intel® Graphics Performance Analyzers option (or similar) in your BIOS and set it to Enabled.

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