Get Started with Intel® Advisor

Set Up Environment

Launch Intel Advisor and Create a Project

To launch the:

• Intel Parallel Studio XE/Intel Advisor standalone GUI:

  • In the Linux* OS: Run the advixe-gui command.

  • In the Windows* OS: From the Microsoft Windows* All Apps screen, select Intel Parallel Studio XE 201n > Intel Advisor 201n

• Intel System Studio/Intel Advisor standalone GUI: Choose Tools > Intel Advisor > Launch > Intel Advisor from the IDE menu.

• Intel Advisor plug-in to the Visual Studio* IDE: Open your solution in the Visual Studio* IDE.

To create an Intel Advisor project:

1. Do one of the following

   • In the standalone GUI: Choose File > New > Project… to open the Create a Project dialog box. Supply a name and location for your project, then click the Create Project button to open the Project Properties dialog box.

   • In the Visual Studio* IDE: Choose Project > Intel Advisor 201n Project Properties... to open the Project Properties dialog box.

2. On the left side of the Analysis Target tab, ensure the Survey Hotspots Analysis type is selected, then set appropriate parameters. (Setting the binary/symbol search and source search directories is optional for the Vectorization Advisor.)

Run Survey Analysis

Under Survey Target in the Vectorization Workflow, click the control to collect Survey data while your application executes. Upon completion the Intel Advisor displays a Survey Report similar to the following.

There are many controls available to help you focus on the data most important to you, including the following:

Investigate Loops

If all loops are vectorizing properly and performance is satisfactory, you are done! Congratulations!

If one or more loops is not vectorizing properly and performance is unsatisfactory:

1. Improve application performance using various Intel Advisor features to guide your efforts, such as:

   • Information in the Performance Issues column and associated Recommendations tab
     
     

     Table of contents on right, showing recommendations for each issue relevant to the loop. Expandable/collapsible recommendations on left (some reference details specific to the analyzed loop, such as vector length or trip count). Number of bars on recommendation icon shows confidence this recommendation is the appropriate fix.

   • Suggestions in Next Steps: After Running Survey Analysis in the Intel Advisor User Guide

   • Optional Dependencies and Memory Access Patterns (MAP) analyses to help you dig deeper

2. Rebuild your modified code.

3. Run another Survey analysis to verify all loops are vectorizing properly and performance is satisfactory.

Learn More About Roofline Charts

The Roofline chart plots an application's achieved performance and arithmetic intensity against the machine's maximum achievable performance:

• Arithmetic intensity (x axis) - measured in number of floating-point operations (FLOPs) and/or integer operations (INTOPs) per byte, based on the loop/function algorithm, transferred between CPU/VPU and memory

• Performance (y axis) - measured in billions of floating-point operations per second (GFLOPS) and/or billions of integer operations per second (GINTOPS)

In general:

• The size and color of each Roofline chart dot represent relative execution time for each loop/function. Large red dots take the most time, so are the best candidates for optimization. Small green dots take less time, so may not be worth optimizing.

• Roofline chart diagonal lines indicate memory bandwidth limitations preventing loops/functions from achieving better performance without some form of optimization. For example: The L1 Bandwidth roofline represents the maximum amount of work that can get done at a given arithmetic intensity if the loop always hits L1 cache. A loop does not benefit from L1 cache speed if a dataset causes it to miss L1 cache too often, and instead is subject to the limitations of the lower-speed L2 cache it is hitting. So a dot representing a loop that misses L1 cache too often but hits L2 cache is positioned somewhere below the L2 Bandwidth roofline.

• Roofline chart horizontal lines indicate compute capacity limitations preventing loops/functions from achieving better performance without some form of optimization. For example: The Scalar Add Peak represents the peak number of add instructions that can be performed by the scalar loop under these circumstances. The Vector Add Peak represents the peak number of add instructions that can be performed by the vectorized loop under these circumstances. So a dot representing a loop that is not vectorized is positioned somewhere below the Scalar Add Peak roofline.

• A dot cannot exceed the topmost rooflines, as these represent the maximum capabilities of the machine; however, not all loops can utilize maximum machine capabilities.

• The greater the distance between a dot and the highest achievable roofline, the more opportunity exists for performance improvement.

In the following Roofline chart representation, loops A and G (large red dots), and to a lesser extent B (yellow dot far below the roofs), are the best candidates for optimization. Loops C, D, and E (small green dots) and H (yellow dot) are poor candidates because they do not have much room to improve or are too small to have significant impact on performance.

The Intel Advisor basic roofline model, the Cache-Aware Roofline Model (CARM), offers self data capability. The Intel Advisor Roofline with Callstacks feature extends the basic model with total data capability:

• Self data = Memory access, FLOPs, and duration related only to the loop/function itself and excludes data originating in other loops/functions called by it

• Total data = Data from the loop/function itself and its inner loops/functions

The total-data capability in the Roofline with Callstacks feature can help you:

• Investigate the source of loops/functions instead of just the loops/functions themselves.

• Get a more accurate view of loops/functions that behave differently when called under different circumstances.

• Uncover design inefficiencies higher up the call chain that could be the root cause of poor performance by smaller loops/functions.

The following Roofline chart representation shows some of the added benefits of the Roofline with Callstacks feature, including:

• A navigable, color-coded Callstack pane that shows the entire call chain for the selected loop/function, but excludes its callees

• Visual indicators (caller and callee arrows) that show the relationship among loops and functions

• The ability to simplify dot-heavy charts by collapsing several small loops into one overall representation

  Loops/functions with no self data are grayed out when expanded and in color when collapsed. Loops/functions with self data display at the coordinates, size, and color appropriate to the data when expanded, but have a gray halo of the size associated with their total time. When such loops/functions are collapsed, they change to the size and color appropriate to their total time and, if applicable, move to reflect the total performance and total arithmetic intensity.

For more information on how to produce, display, and interpret the Roofline with Callstacks extension to the Roofline chart, see Roofline with Callstacks.

There are several controls to help you show/hide the Roofline chart:

There are several controls to help you focus on the Roofline chart data most important to you, including the following.

Set Up Environment

Launch Intel Advisor and Create a Project

To launch the:

• Intel Parallel Studio XE/Intel Advisor standalone GUI:

  • In the Linux* OS: Run the advixe-gui command.

  • In the Windows* OS: From the Microsoft Windows* All Apps screen, select Intel Parallel Studio XE 201n > Intel Advisor 201n

• Intel System Studio/Intel Advisor standalone GUI: Choose Tools > Intel Advisor > Launch > Intel Advisor from the IDE menu.

• Intel Advisor plug-in to the Visual Studio* IDE: Open your solution in the Visual Studio* IDE.

To create an Intel Advisor project:

1. Do one of the following

   • In the standalone GUI: Choose File > New > Project… to open the Create a Project dialog box. Supply a name and location for your project, then click the Create Project button to open the Project Properties dialog box.

   • In the Visual Studio* IDE: Choose Project > Intel Advisor 201n Project Properties... to open the Project Properties dialog box.

2. On the left side of the Analysis Target tab, ensure the Survey Hotspots Analysis type is selected and set appropriate parameters.

3. Set appropriate parameters for other analysis types and tabs. (Setting the binary/symbol search and source search directories is optional for the Vectorization Advisor.)

Run Roofline Analysis

Under Run Roofline in the Vectorization Workflow, click the control to execute your target application. Upon completion, the Intel Advisor displays a Roofline chart.

To implement the Roofline with Callstacks feature:

1. Run the Roofline analysis with the With Callstacks checkbox enabled. Upon completion, the Intel Advisor displays a Roofline chart.

2. Enable the With Callstacks checkbox in the Roofline chart.

Investigate Loops

If all loops are vectorizing properly and performance is satisfactory, you are done! Congratulations!

If one or more loops is not vectorizing properly and performance is unsatisfactory:

1. Check data in associated Intel Advisor views to support your Roofline chart interpretation. For example: Check the Vectorized Loops/Efficiency values in the Survey Report or the data in the Code Analytics tab.

2. Improve application performance using various Intel Advisor features to guide your efforts, such as:

   • Information in the Performance Issues column and associated Recommendations tab
     
     

     Table of contents on right, showing recommendations for each issue relevant to the loop. Expandable/collapsible recommendations on left (some reference details specific to the analyzed loop, such as vector length or trip count). Number of bars on recommendation icon shows confidence this recommendation is the appropriate fix.

   • Information in the Why No Vectorization? column and associated Why No Vectorization? tab

   • Suggestions in Next Steps: After Running Survey Analysis in the Intel Advisor User Guide

If you need more information, continue your investigation by:

1. Marking one or more loops/functions for deeper analysis in the column AND

2. Running a Dependencies analysis to discover why the compiler assumed a dependency and did not vectorize a loop/function, and/or running a Memory Access Patterns (MAP) analysis to identify expensive memory instructions

Run Dependencies Analysis

To run a Dependencies analysis:

1. Mark one or more un-vectorized loops for deeper analysis in the column in the Survey Report.

2. Under Check Dependencies in the Vectorization Workflow, click the control to collect Dependencies data while your application executes.

After the Intel Advisor collects the data, it displays a Dependencies-focused Refinement Report similar to the following:

There are many controls available to help you focus on the data most important to you, including the following:

If the Dependencies Report shows:

• There is no real dependency in the loop for the given workload, follow Intel Advisor guidance to tell the compiler it is safe to vectorize.

• There is an anti-dependency (often called a Write after read dependency or WAR), follow Intel Advisor guidance to enable vectorization.

Intel Advisor code improvement guidance is available in the Recommendations tab and Next Steps: After Running Survey Analysis in the Intel Advisor User Guide. After you finish improving your code:

1. Run a Memory Access Patterns (MAP) analysis if desired.

2. Rebuild your modified code.

3. Run another Roofline analysis to verify your application still runs correctly and all test cases pass, all loops are vectorizing properly, and performance is satisfactory.

Run Memory Access Patterns (MAP) Analysis

To run a Memory Access Patterns (MAP) analysis:

1. Mark one or more un-vectorized loops for deeper analysis in the column in the Survey Report.

2. Under Check Memory Access Patterns in the Vectorization Workflow, click the control to collect MAP data while your application executes.

After the Intel Advisor collects the data, it displays a MAP-focused Refinement Report similar to the following:

Intel Advisor code improvement guidance is available in the Recommendations tab and Next Steps: After Running Survey Analysis in the Intel Advisor User Guide. After you finish improving your code:

1. Rebuild your modified code.

2. Run another Roofline analysis to verify your application still runs correctly and all test cases pass, all loops are vectorizing properly, and performance is satisfactory.

Set Up Environment

Launch Intel Advisor and Create a Project

To launch the:

• Intel Parallel Studio XE/Intel Advisor standalone GUI:

  • In the Linux* OS: Run the advixe-gui command.

  • In the Windows* OS: From the Microsoft Windows* All Apps screen, select Intel Parallel Studio XE 201n > Intel Advisor 201n

• Intel System Studio/Intel Advisor standalone GUI: Choose Tools > Intel Advisor > Launch > Intel Advisor from the IDE menu.

• Intel Advisor plug-in to the Visual Studio* IDE: Open your solution in the Visual Studio* IDE.

To create an Intel Advisor project:

1. Do one of the following

   • In the standalone GUI: Choose File > New > Project… to open the Create a Project dialog box. Supply a name and location for your project, then click the Create Project button to open the Project Properties dialog box.

   • In the Visual Studio* IDE: Choose Project > Intel Advisor 201n Project Properties... to open the Project Properties dialog box.

2. On the left side of the Analysis Target tab, ensure the Survey Hotspots Analysis type is selected and set appropriate parameters.

3. Set appropriate parameters for other analysis types and tabs. (Setting the binary/symbol search and source search directories is required for the Threading Advisor.)

Run Survey Analysis

Under Survey Target in the Threading Workflow, click the control to collect Survey data while your application executes. Use the resulting information to discover candidates for parallelization with threads.

Investigate Loops

Pay particular attention to the hottest loops in terms of Self Time and Total Time. Optimizing these loops provides the most benefit. Outermost loops with significant Total Time are often good candidates for parallelization with threads. Innermost loops and loops near innermost loops are often good candidates for vectorization.

Annotate Sources

Insert annotations to mark places in parts of your application that are good candidates for later replacement with parallel framework code that enables parallel execution.

The main types of Intel Advisor annotations mark the location of:

• A parallel site. A parallel site is a region of code that contains one or more tasks that may execute in one or more parallel threads to distribute work. An effective parallel site typically contains a hotspot that consumes application execution time. To distribute these frequently executed instructions to different tasks that can run at the same time, the best parallel site is not usually located at the hotspot, but higher in the call tree.

• One or more parallel tasks within a parallel site. A task is a portion of time-consuming code with data that can be executed in one or more parallel threads to distribute work.

• Locking synchronization, where mutual exclusion of data access must occur in the parallel application.

The Intel Advisor User Guide offers sample annotated source code you can copy into your editor include:

After inserting annotations, rebuild your application in release mode.

Run Suitability Analysis

Under Check Suitability in the Threading Workflow, click the control to collect Suitability data while your application executes.

The Suitability Report predicts maximum speedup based on the inserted annotations and what-if modeling parameters with which you can experiment, such as:

• Different hardware configurations and parallel frameworks

• Different trip counts and instance durations

• Any plans to address parallel overhead, lock contention, or task chunking when you implement your parallel framework code

Use the resulting information to choose the best candidates for parallelization with threads.

Run Dependencies Analysis

Under Check Dependencies in the Threading Workflow, click the control to collect Dependencies data while your application executes. Use the resulting information to fix the data sharing problems if the predicted maximum speedup benefit justifies the effort.

Improve App Performance

If you decide the predicted maximum speedup benefit is worth the effort to add threading parallelism to your application:

1. Complete developer/architect design and code reviews about the proposed parallel changes.

2. Choose one parallel programming framework (threading model) for your application, such as Intel® Threading Building Blocks (Intel® TBB), OpenMP*, Microsoft Task Parallel Library* (TPL), or some other parallel framework.

3. Add the parallel framework to your build environment.

4. Add parallel framework code to synchronize access to the shared data resources, such as Intel TBB or OpenMP* locks.

5. Add parallel framework code to create parallel tasks.

As you add the appropriate parallel code from the chosen parallel framework, you can keep, comment out, or replace the Intel Advisor annotations.

No Shared Drive

Follow these steps if you cannot put the target application (binaries, symbol information, source code, etc.) on a shared drive visible to both the remote and the macOS* machines:

1. Install only the Intel Advisor GUI on the macOS* machine.

2. Install the Intel Advisor on the remote machine. You may install the complete tool or a portion of the tool, such as only the CLI if you plan to collect data using only the CLI.

3. On the remote machine:

   • Build an optimized binary of your application in release mode using settings designed to produce the most accurate and complete analysis results. See the Before You Begin section in this document for detailed settings.

   • Set up the environment, launch the Intel Advisor, create a project, and collect the desired data. Check the other workflow sections in this document for detailed instructions.

   • Do one of the following to create an Intel Advisor snapshot of the collected data:

     • In the GUI, click the icon. See Create a Result Snapshot Dialog Box in the Intel Advisor User Guide for detailed instructions.

     • in the CLI, use the advixe-cl --snapshot command. See the Automate Workflows section in this document for a sample command line.

     Make sure you pack both sources and binaries in a zip archive file.

   • Copy the resulting .advixeexpz file to the macOS* machine.

4. On the macOS* machine:

   • Set up the environment by running one of the following source commands: source <advisor-install-dir>/advixe-vars.csh or source <advisor-install-dir>/advixe-vars.sh.

   • Launch the Intel Advisor.

   • Open the .advixeexpz file result using the File > Open > Result menu option.

Shared Drive

Follow these steps if you can put the target application (binaries, symbol information, and source code) on a shared drive visible to both the remote and the macOS* machines:

1. Install only the Intel Advisor GUI on the macOS* machine.

2. Install the Intel Advisor on the remote machine. You may install the complete tool or a portion of the tool, such as only the CLI if you plan to collect data using only the CLI.

3. On the shared drive: Build an optimized binary of your application in release mode using settings designed to produce the most accurate and complete analysis results. See the Before You Begin section in this document for detailed settings.

4. On the remote machine:

   • Set up the environment and launch the Intel Advisor. Check the other workflows in this document for detailed instructions.

   • Set the result location to the shared drive using File > Options > Result Location.

   • Create a project that points to the shared drive and collect the desired data. Check the other workflows in this document for detailed instructions.

5. On the macOS* machine:

   • Set up the environment by running one of the following source commands: source <advisor-install-dir>/advixe-vars.csh or source <advisor-install-dir>/advixe-vars.sh.

   • Launch the Intel Advisor.

   • Open the .advixeexp file on the shared drive using the File > Open > Result menu option.

Set Up Environment

Command Line

This section shows how to get started using the Intel Advisor CLI. The main advantage of using the Intel Advisor CLI instead of the GUI is you can perform analysis and collect data as part of an automated or background task, and then view the result in a CLI report (or in the GUI) at your convenience.

Below are examples of typical Intel Advisor CLI tasks.

MPI

This section shows how to get started using the Intel Advisor in an MPI environment.

You can perform an MPI analysis only through the Intel Advisor CLI; however, there are several ways to view an Intel Advisor result:

• If you have an Intel Advisor GUI in your cluster environment, open a result in the GUI.

• If you do not have an Intel Advisor GUI on your cluster node, copy the result directory to another machine with the Intel Advisor GUI and open the result there.

• Use the Intel Advisor command line reports to browse results on a cluster node.

Use mpirun, mpiexec, or your preferred MPI batch job manager with the advixe-cl command to start an analysis. You may also use the -gtool option of mpirun. See the Intel® MPI Library Reference Manual (available in the Intel® Software Documentation Library) for more information.

Below are examples of typical Intel Advisor MPI tasks.