User Guide


Group and Filter Data

Analyze the data collected with the
Intel® VTune™
by filtering in areas of interest and grouping the data by specific program units (modules, functions, frame domains, and so on).
provides powerful filtering mechanisms that enable you to focus on specific objects or time regions. This helps you focus only on the areas of interest and at the same time speeds up the GUI response when a smaller data set is processed.

Filter by Objects

To filter by particular program units (functions, modules, and so on), use any of the following options:
  • Context menu options
    : Select objects of interest in the grid, right-click and choose the
    Filter In by Selection
    context menu option to exclude all objects from the view other than the objects you selected. And conversely, choosing the
    Filter Out by Selection
    hides the selected data. The filter bar at the bottom is updated to show the percentage of the displayed data by a certain metric.
    For example, you want to filter in the grid by the most time-consuming function
    When the filter is applied, the filter bar shows that you see only 24.9% of the collected CPU Time data.
  • Filter toolbar options
    : Select a program unit in the filtering drop-down menu (process, module, thread) to filter out your grid and Timeline view for displaying the data for this particular program unit. For example, if you select the
    process introducing 51.5% of the CPU Time, the result data will display statistics for this module only and the filter bar provides an indicator that only 51354% of the CPU Time data is currently displayed:

Filter by Time Regions

You can narrow down your analysis to particular regions on the timeline. For example, you may select an area of interest on the Timeline pane in the GPU Compute/Media Hotspots viewpoint, right-click and select the
Zoom In by Selection
Zoom In and Filter In by Selection
context menu option:
The context summary on the right will be updated for the selected time range and the filter toolbar will show the percentage of the data (per the default metric for this viewpoint) displayed.

Group Data

You can organize a view to focus on the sequence of data you need using the
menu. The available groups depend on the analysis type and viewpoint:
Grouping Drop-down Menu
For example, if you want to view the collected data for the modules you develop, you may select the
Module/Function/Call Stack
granularity, identify the hottest functions in your modules, and then switch to the
Function/Thread/Logical Core/Call Stack
granularity to see which CPUs your hot functions were running on.
provides a set of pre-configured granularities that could be semantically divided into the following groups:
Groups targeted for analysis
Identify function hotspots and distinguish problem call stacks.
For most viewpoints, Function level is the default. If application modules have debug information, you can rely on functions shown as hotspots. When debug information is incomplete or missing, you may see a number of
functions, or samples collected on internal functions of a module might be attributed to adjacent exported functions.
Function/Call Stack
Source Function/Function/Call Stack
for analyzing all instances of the inline and JITed functions
Multi-threading analysis
Analyze hotspots in multi-threaded applications from the function, OS (Threads) or HW (Packages, Core, Threads) perspectives.
Function/Thread/Logical Core/Call Stack
for detecting anomalies of the function execution on different threads
Function/Package/Logical Core/Thread/Call Stack
for identifying Interconnect/NUMA issues on multi-processor systems
Physical Core/Logical Core/Function/Call Stack
for identifying specific hyper-threading issues
Physical Core/Thread/Function/Call Stack
Thread/Physical Core/Function
for identifying issues caused by thread migration between cores
Frame analysis
Frame Domain/Frame Duration Type/Function/Call Stack
Frame Domain/Frame Duration Type/Frame/Function/Call Stack
OpenMP* analysis
Identify hotspots called from OpenMP regions.
OpenMP Region/OpenMP Barrier-to-Barrier Segment/Function/Call Stack
for identifying load imbalance between different segments
OpenMP Region/OpenMP Region Duration Type/Function/Call Stack
for analyzing fast/slow OpenMP region instances
GPU analysis
Analyze the CPU activity while the GPU was either idle or executing some code
Render and GPGPU Packet Stage / Function / Call Stack
Render and GPGPU Packet Stage / Thread / Function / Call Stack
Typically, you start your analysis with the
window where clicking an object of interest opens the grid pre-grouped in the most convenient way for analysis.
If the pre-configured grouping levels do not suit your analysis purposes, you can create your own grouping levels by clicking the
Customize Grouping
button and configuring the Custom Grouping dialog box.

Product and Performance Information


Performance varies by use, configuration and other factors. Learn more at