Intel® Trace Analyzer and Collector

Understand MPI application behavior, quickly finding bottlenecks, and achieving high performance for parallel cluster applications

  • Powerful MPI Communications Profiling and Analysis
  • Scalable - Low Overhead & Effective Visualization
  • Flexible to Fit Workflow – Compile, Link or Run

Intel® Trace Analyzer and Collector 9.0 is a graphical tool for understanding MPI application behavior, quickly finding bottlenecks, improving correctness, and achieving high performance for parallel cluster applications based on Intel architecture. Improve weak and strong scaling for small and large applications with Intel Trace Analyzer and Collector.


  • Visualize and understand parallel application behavior
  • Evaluate profiling statistics and load balancing
  • Analyze performance of subroutines or code blocks
  • Learn about communication patterns, parameters, and performance data
  • Identify communication hotspots
  • Decrease time to solution and increase application efficiency

MPI checking

  • A unique MPI Correctness Checker detects deadlocks, data corruption, and errors with MPI parameters, data types, buffers, communicators, point-to-point messages and collective operations.
  • The Correctness Checker allows the user to scale to extremely large systems and detect errors even among a large number of processes.

Interface and Displays

  • Intel® Trace Analyzer and Collector includes full-color customizable GUI with many drill-down view options.
  • The analyzer is able to extremely rapidly unwind the call stack and use debug information to map instruction addresses to source code.
  • With both command-line and GUI interfaces, the user can additionally set up batch runs or do interactive debugging.


  • Low overhead allows random access to portions of a trace, making it suitable for analyzing large amounts of performance data.
  • Thread safety allows you to trace multithreaded MPI applications for event-based tracing as well as non-MPI threaded applications.

Instrumentation and Tracing

  • Low-intrusion instrumentation supports MPI applications with C, C++, or Fortran.
  • Intel Trace Analyzer and Collector automatically records performance data from parallel threads in C, C++, or Fortran

What’s new

  • MPI Communications Profile Summary Overview
    • Quickly Understand Computation vs Communications
    • Identify which MPI communications are being most used
    • Advice of where to start your analysis

  • Expanded Standards Support with MPI 3.0
    • Automated MPI Communications Analysis with Performance Assistant
    • Detect common MPI performance issues
    • Automated tips on potential solutions

Videos to help you get started.

Register for future Webinars

Previously recorded Webinars:

  • Increase Cluster MPI Application Performance with a "MPI Tune" Up
  • MPI on Intel® Xeon Phi™ coprocessor
  • Quickly discover performance issues with the Intel® Trace Analyzer and Collector 9.0 Beta

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MPI Library Runtime Enviroment 4.0
Par Pablo V.1
Hello, I am working by using remote deskpot of Cornell University servers and I have not internet conection in my deskpot. I am using Visual Studios 2008 with Intel Visual Fortran Composer XE 2011, and supposedly it has already installed MPI Library Runtime Enviroment 4.0 I can´t find the files msmpi.lib or impi.lib, or the include path. Nevertheless, I found the folder with other files like mpichi2mpi.dll, impi.dll, impimt.dll,mpiexec.ex, wmpiexec.exe, etc. The package ID in the support file is w_mpi_rt_p_4.0.1.007 listed    How can I include .dll mpi files to my code?  Thanks,
how to run the hybrid MPI/OpenMP
Par dingjun.chencmgl.ca1
Hi, Dear Sir or Madam, I am using the Intel MPI and OpenMP and Intel Composer XE 2015 to build a hybrid MPI/OpenMP application. For example, if I want to run the executable file of my application on 3 SMP computers with 3 MPI processes and each MPI process consists of 16 OpenMP threads.  Our PC cluster has 3 SMP nodes connected by the Infiniband and each node has 16 cores.   Could someone tell me how to run with the Intel MPI command: mpiexec.exe in order to implement above running way? where can I find such a study guide for running with Intel MPI?  I look forward to hearing from you and your reply is highly appreciated. Thanks in advance.      
Error message: control_cb (./pm/pmiserv/pmiserv_cb.c:1151): assert (!closed) failed
Par L. Juan1
Hello, I have the following error message when I run my FORTRAN code on a HPC of my university: [mpiexec@node0653] control_cb (./pm/pmiserv/pmiserv_cb.c:1151): assert (!closed) failed I had my code attached. I can successfully compile my codes in debug mode without any error. Besides, I have already unblocked the stack size of my machine by adding in command line "ulimit -a unlimited."  To replicate the error message, please use the attached makefile to built the program, keep all the .txt files in the same folder, and then in command line type "mpirun -np 32 ./main" to execute the program. Roughly after 5 to 10 minutes, you would see the unexpected termination of the program and the machine should issue the error message as seen above. Please help me with the problem. Thanks. Lee    
Intel MPI process placement
Par Wadud M.3
Hello, I would like to pin MPI processes across all CPU sockets. For example, I would like to run 10 MPI processes on a two socket machine with 5 MPI processes on each socket. Could you please send me the instructions on doing this? Many thanks,
IPM Statistics Format: GFLOPS is Missing
Par Srikanth Yalavarthi1
I have been trying to collect mpi statistics of my application and have been using the following settings   export I_MPI_STATS=ipm export I_MPI_STATS_SCOPE="all2all;all2one;one2all;comm;io;sync;time" ################################################################################ # # command : ./test.exe (completed) # host    : asn5/x86_64_Linux             mpi_tasks : 16 on 1 nodes # start   : 01/01/15/10:47:28               wallclock : 52.170432 sec # stop    : 01/01/15/10:48:20               %comm     : 36.61 # gbytes  : 0.00000e+00 total               gflop/sec : NA # ################################################################################ # region  : *   [ntasks] = 16 # #                         [total]       <avg>         min           max # entries                 16            1             1             1              # wallclock               834.094       52.1309       52.1115       52.1704        # user                    816.428       51.0267...
filehandle value problem MPI MPI_FILE_OPEN on Windows
Par Angel B.0
Testing the Intel MPI libraries in windows 8.1.  I encounter some problems in the following statement. call MPI_FILE_OPEN(MPI_COMM_WORLD, filename, MPI_MODE_WRONLY + MPI_MODE_CREATE, MPI_INFO_NULL, fh, ierror) I get return values for fh looking like this  -1212974328,  What's going on?
Trouble with checkpointing with Intel MPI using blcr
Par hrscad d.0
Trying to run checkpointing with BLCR using the Intel MPI library. Compiled the source MPI codes using the Intel mpicc compiler.  While running, used mpiexec.hydra -ckpoint on -ckpointlib blcr and other options. The checkpoints do get written, but the application crashes with a segfault after the first checkpoint itself (after having written a multi gigabyte checkpoint context file to disk). The applications run perfectly to completion when I run them without the checkpoint options. Also, checkpointing runs without problem when run on single node with multiple MPI processes. The commandline options I use to launch the jobs are: mpiexec.hydra -genv I_MPI_FABRICS shm:ofa -machinefile ./nodes -n 24 -ckpoint on -ckpointlib blcr -ckpoint-interval 300 ./MPIJob What might be going wrong here?         Detailed outputs are given below: # mpiexec.hydra -genv I_MPI_FABRICS shm:ofa -machinefile ./nodes -n 24 -ckpoint on -ckpointlib blcr -ckpoint-interval 300 ./lmp_linux -var x 120 -v...
Problem on MPI: About Non-Blocking Collective operations
Par Mingqing W.0
  The structure of my code is, //part1 if(i>1){           Compute1;         } //part2 if(i<m)       {            Compute2;          MPI_Allgatherv();  //Replaced by MPI_Iallgatherv();        } //part3 if(i>0)      {          Compute3;          MPI_Allreduce();      } part4 if(i<m){          Compute4;          } Collective operations in part 2 is the bottleneck of this program. I replaced "MPI_Allgatherv()" by the NBC "MPI_Iallgatherv()" in order to hide the collective communication by part3 and part4. But part3 and part4 take much longer than before. What do you think is the cause of this problem? Thanks!
S’abonner à Forums
  • What are some key things I can learn about my program using Intel® Trace Analyzer and Collector?
  • The Intel Trace Analyzer and Collector is a graphical tool used primarily for MPI-based programs. It helps you understand your application's behavior across its full runtime. It can help find temporal dependencies in your code and communication bottlenecks across the MPI ranks. It also checks the correctness of your application and points you to potential programming errors, buffer overlaps, and deadlocks.

  • Will Intel Trace Analyzer and Collector only work with Intel MPI Library?
  • No, the Intel Trace Analyzer and Collector support all major MPICH2-based implementations. If you're wondering whether your MPI library can be profiled using the Intel Trace Analyzer and Collector, you can run a simple ABI-compatibility check by compiling the provided mpiconstants.c file and verifying the values with the ones provided in the Intel Trace Collector Reference Guide..

  • Can Intel Trace Analyzer and Collector be used on applications for Intel® Many Integrated Core Architecture (Intel® MIC Architecture)?
  • Yes, Intel MIC Architecture is fully supported by the Intel Trace Analyzer and Collector.

  • What file and directory permissions are required to use Intel Trace Analyzer and Collector?
  • You do not need to install special drivers, kernels, or acquire extra permissions. Simply install the Intel Trace Analyzer and Collector in the $HOME directory and link it with your application of choice from there.

  • Should I recompile/relink my application to collect information?
  • It depends on your application. For Windows* OS, you have to relink your application by using the –trace link-time flag.

    For Linux* OS (and if your application is dynamically linked), you do not need to relink or recompile. Simply use the –trace option at runtime (for example: mpirun –trace).

  • How do I control which part of my application should be profiled?
  • The Intel Trace Collector provides several options to control the data collection. By default, only information about MPI calls is collected. If you'd like to filter which MPI calls should be traced, create a configuration file and set the VT_CONFIG environment variable.

    If you'd like to expand the information collected beyond MPI and include all user-level routines, recompile your application with the –tcollect switch available as part of the Intel® Compilers. In this case, Intel Trace Collector will gather information about all routines in the application, not just MPI. You can similarly filter this via the –tcollect-filter compiler option.

    If you'd like to be explicit about which parts of the code should be profiled, use the Intel Trace Collector API calls. You can manually turn tracing on and off via a quick API call.

    For more Information on all of these methods, refer to the Intel Trace Collector Reference Guide..

  • What file format is the trace data collected in?
  • Intel Trace Collector stores all collected data in Structured Tracefile Format (STF) which allows for better scalability across both time and processes. For more details, refer to the "Structured Tracefile Format" section of Intel Trace Collector Reference Guide.

  • Can I import or export trace data to/from Intel Trace Analyzer and Collector?
  • Yes, you can export the data from any of the Profile charts (Function Profile, Message Profile, and Collective Operations Profile) as part of the Intel Trace Analyzer interface. To do this, open one of these profiles in the GUI, right-click to bring up the Context Menu, and select the "Export Data" option. The data will be saved in simple text format for easy reading.

    At a separate level, you can save your current working Intel Trace Analyzer environment via the Project Menu. If you choose to "Save Project", your current open trace view and associated charts will be recorded as they are open on your screen. You can later choose to "Load Project" from this same menu, which will bring up a previously-saved session.

  • What size MPI application can I analyze with Intel Trace Analyzer and Collector?
  • It depends on how large or complex your application is, how many MPI calls you are making, and for how long you are running. There are no internal limitations on the size of the MPI job but there are plenty of external ones. It all depends on how much memory is available on the system (per core) both for the application, the MPI library, and for the Intel Trace Collector processes, as well as disk space availability. Any additional flags enabled (for example, storing call stack and source code locations) cause an increase in the size of the trace file. Filtering out unimportant information is always a good solution to reducing trace files.

  • How can I control the amount of data collected to a reasonable amount? What is a reasonable amount?
  • Each application is different in terms of the profiling data it can provide. The longer an application runs, and the more MPI calls it makes, the larger the STF files will be. You can filter some of the unnecessary information out by applying appropriate filters (see Question #6 for more details or check out some tips on Intel Trace Collector Filtering).

    Additionally, you can be restricted by the resources allocated to your account; consult your cluster administration about quotas and recommendations.

  • How can I analyze the collected information?
  • Once you have collected the trace data, you can analyze it via the Graphical Interface called the Intel Trace Analyzer. Simply call the command ($ traceanalyzer) or double-click on the Intel Trace Analyzer icon and navigate to your STF files via the File Menu.

    You can get started by opening up the Event Timeline chart (under the Charts Menu) and zooming in at an appropriate level.

    Check out the Detecting and Removing Unnecessary Serialization Tutorial on ideas how to get started. For details on all Intel Trace Analyzer functionality, refer to the Intel Trace Analyzer Reference Guide.

  • Can I use Intel Trace Analyzer and Collector with Intel® VTune™ Amplifier XE, Intel® Inspector XE, or other analysis tools?
  • While these tools would collect information separate from each other, in their own format, it's easy enough to use the Intel VTune Amplifier XE and Intel Inspector XE tools under an MPI environment. Check each tool's respective User's Guide for more info on Viewing Collected MPI Data.

    You can use tools such as Intel VTune Amplifier XE and Intel Inspector XE for node-level analysis, and use the Intel Trace Analyzer and Collector for cluster-level analysis.

Intel® Trace Analyzer & Collector

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