Defines how dotTrace will collect profiling data. The following table will help you to choose a suitable profiling type. For more details, refer to Basic Concepts.
|Sampling||Accurate time measurement, number of calls is not measured.|
Recommended for most cases. Ideal when you look for performance issues in your app for the first time.
|Tracing||Accurate calls count measurement, time measurement may be inaccurate due to profiling overhead.||When sampling data is not enough. For example, for analyzing algorithm complexity (when info about number of calls is more valuable than call time values).|
|Line-by-line||Each line of code is measured, call time values are inaccurate due to huge profiler overhead. |
To lower the overhead, you can profile only particular methods using filters.
|For advanced use cases only. For example, when you already know what function causes issues and want to analyze each line of it.|
|Timeline||Collects temporal data about thread states, application events, and other multi-threading data. Based on Event Tracing for Windows (ETW).|
Recommended for most cases. Especially, for analyzing multithreaded apps. Use it, for example, to determine the cause of UI freezes, excessive garbage collections, uneven workload distribution, insufficient I/O, and so on.
Collect profiling data from start
If selected, dotTrace will start recording profiling data right after the launch. Otherwise, dotTrace will start collecting these data only after you click Start in the Performance Controller window.
If Advanced is selected, you are able to additionally specify the following profiler options:
This option defines how dotTrace must calculate calls time. Typically, this is a choice between whether dotTrace should calculate time when a thread is not working or should not. For more details, refer to Time Measurement Methods.
Real time (performance counter) Recommended. dotTrace calculates the overall real time passed between method entry and exit. This time does not depend on app threads states. Time is calculated using system performance counter. Real time (CPU instruction) dotTrace calculates the overall real time passed between method entry and exit. This time does not depend on app threads states. Time is calculated using the CPU register. Thread time dotTrace calculates only the time when a certain thread is running. The time when the thread is waiting or sleeping is not included in calculation. Thread cycle time dotTrace calculates only the time when a certain thread is running. The time when the thread is waiting or sleeping is not included in calculation. Time is calculated using the CPU register.
The table next in this section will help you to choose a time measurement method better suitable for your case.
(Tracing, Line-by-line) Clear this option if you want dotTrace to turn off JIT-inlining and get call stacks that closely resemble the structure of application's source code.
(Tracing, Line-by-line) If selected, dotTrace will take into account time spent in profiler itself by taking more time samples.
Enable native profiling
(Timeline, Unity/Mono on Windows) If selected, dotTrace will collect native call stack data. The resulting snapshot will contain both managed and native call stacks. This profiling option may be helpful for finding performance issues in Unity games.
Collect native allocations
(Timeline) If selected, dotTrace will collect information about all memory allocations the profiled application does in the native (unmanaged) heap. To be able to select this option, you must have Windows Performance Toolkit installed on your computer.
Collect debug output
(Timeline) If selected, dotTrace will collect information about all messages the profiled application sends to the debug output.
Collect TPL events
(Timeline) If selected, profiling performance may be affected but dotTrace will collect Task Parallel Library (TPL) data. If cleared, there will be no
Tasknodes in Call Tree and
asynccall nodes will lack their await and continuations parts. Learn more about how dotTrace works with asynchronous code in Analyzing Async Calls.
Clear this option in case your application does not use multitasking or you do not need this info.
Use profiler API
Enables you to control profiling directly from the code of the profiled application. For example, to take a snapshot in the exact point of your code. Learn more about using the API in Controlling Profiling Process Through API.
Optimizing Line-by-Line profiling with filters
Line-by-line profiling may be effective in particular cases but it is always time-consuming. To somehow minimize the profiling overhead, you can define some rules. According to them, not all functions are profiled line by line but only those that are really interesting for further investigation.
So you can create and set a filter or filters that match only the functions you need.
To create a new filter
Click Advanced to see advanced profiling options.
Click the Edit Filters button.
Click Add Filter in the Profiling Filters dialog.
For more information about the dialog, see Dialogs: Profiling Filters.
In the Add Filter dialog, choose the type of filter rule:
Profile code in - to include the specified code item into profiling and exclude all other code items.
Do not profile code in - to exclude the specified code item from profiling.
Do not profile code marked with attribute - to exclude code items with the specified attribute from profiling.
If you have chosen one of the first two options, specify an assembly, a class, and/or a method to be included or excluded from profiling. Code items are filtered independently on one another. For example, if you specify a method and leave asterisks (*) for assembly and class to exclude methods with the specified name from all assemblies and all classes.
If you have chosen the last option, specify the name of the attribute that will be used to exclude symbols from profiling. Optionally, specify the assembly name where this attribute is declared.
Click OK to finish adding the filter.
In the Profiling Filters dialog, click Save to save and apply your modifications.
At any time you can modify the pattern defined for a filter and vary what filters to apply from session to session.