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.

Benefits:

  • 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.

Scalability

  • 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:

  • Fast, light weight, scalable MPI performance analysis
  • 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

More Tech Articles

Intel® Trace Analyzer and Collector Structured Tracefile Format
By Gergana Slavova (Intel)Posted 04/14/20150
The Intel® Trace Analyzer and Collector employs the use of the Structured Trace File Format (STF) in order to profile MPI applications in a scalable and efficient manner. The development of STF was motivated by the observation that the conventional approach of handling trace data in a single tra...
Using Intel® MPI Library 5.0 with MPICH based applications
By Dmitry Sivkov (Intel)Posted 08/25/20140
Why it is needed? Different MPI implementations have their specific benefits and advantages. So in the specific cluster environment the HPC application with the other MPI implementation can probably perform better.  Intel® MPI Library has the following benefits: Support of the wide range of cl...
Intel® Cluster Tools Open Source Downloads
By Gergana Slavova (Intel)Posted 03/06/20140
This article makes available third-party libraries and sources that were used in the creation of Intel® Software Development Products. Intel provides this software pursuant to their applicable licenses. Products and Versions: Intel® Trace Analyzer and Collector for Linux* gcc-3.2.3-42.zip (whi...
Using the Intel® MPI Library on Intel® Xeon Phi™ Coprocessor Systems
By loc-nguyen (Intel)Posted 03/19/201316
Download Article Download Using_Intel_MPI_on_Intel_Xeon_Phi_Coprosessor_Systems-v1_4.pdf  [PDF 548KB] Table of Contents Chapter 1 – Introduction 1.1 – Overview 1.2 – Compatibility Chapter 2 – Installing the Intel® MPI Library 2.1 – Installing the Intel MPI Library 2.2 – Preparat...
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Supplemental Documentation

Intel® Parallel Studio XE 2015 Update 3 Cluster Edition Readme
By Gergana Slavova (Intel)Posted 04/24/20150
The Intel® Parallel Studio XE 2015 Update 3 Cluster Edition for Linux* and Windows* combines all Intel® Parallel Studio XE and Intel® Cluster Tools into a single package. This multi-component software toolkit contains the core libraries and tools to efficiently develop, optimize, run, and distrib...
Intel® Parallel Studio XE 2015 Update 2 Cluster Edition Readme
By Gergana Slavova (Intel)Posted 02/06/20150
The Intel® Parallel Studio XE 2015 Update 2 Cluster Edition for Linux* and Windows* combines all Intel® Parallel Studio XE and Intel® Cluster Tools into a single package. This multi-component software toolkit contains the core libraries and tools to efficiently develop, optimize, run, and distrib...
Intel® Parallel Studio XE 2015 Update 1 Cluster Edition Readme
By Gergana Slavova (Intel)Posted 11/24/20140
The Intel® Parallel Studio XE 2015 Update 1 Cluster Edition for Linux* and Windows* combines all Intel® Parallel Studio XE and Intel® Cluster Tools into a single package. This multi-component software toolkit contains the core libraries and tools to efficiently develop, optimize, run, and distrib...
Intel® Parallel Studio XE 2015 Cluster Edition Initial Release Readme
By Gergana Slavova (Intel)Posted 08/15/20140
The Intel® Parallel Studio XE 2015 Cluster Edition for Linux* and Windows* combines all Intel® Parallel Studio XE and Intel® Cluster Tools into a single package. This multi-component software toolkit contains the core libraries and tools to efficiently develop, optimize, run, and distribute paral...
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Intel® Parallel Studio XE 2016 Beta program has started!
By Gergana Slavova (Intel)0
The Intel® Parallel Studio XE 2016 Beta program is now available! In this beta test, you will have early access to Intel® Parallel Studio XE 2016 products and the opportunity to provide feedback to help make our products better. Registration is easy through the pre-Beta survey site. This suite of products brings together exciting new technologies along with improvements to Intel’s existing software development tools: Expanded Standards and Features – Scaling Development Efforts Forward Additional language support for C11 and C++14, Fortran 2008 Submodules and IMPURE ELEMENTAL, and C Interoperability from Fortran 2015, and OpenMP* 4.1 TR 3.  New support for SIMD operator use with SSE integer types, Intel® Cilk™ Plus combined Parallel and SIMD loops, OpenMP* 4.0 user-defined reductions (C++ only), enhanced uninitialized variable detection (Fortran only), feature improvements to Intel’s Language Extensions for Offload, annotated source listings, and a new directory structure.  All a...
mpitune Relies on Old OpenSSL
By Ben1
One of our users has reported a problem with the mpitune utility included with Intel MPI v5.0.2.044. In particular, it appears that the hashlib module it uses is linked against an old version of OpenSSL that is not available in our CentOS 6 operating system.
Problem with Intel MPI on >1023 processes
By Jack S.4
I have been testing code using Intel MPI (version 4.1.3  build 20140226) and the Intel compiler (version 15.0.1 build 20141023) with 1024 or more total processes. When we attempt to run on 1024 or more processes we receive the following error:  MPI startup(): ofa fabric is not available and fallback fabric is not enabled  Anything less than 1024 processes does not produce this error, and I also do not receive this error with 1024 processes using OpenMPI and GCC. I am using the High Performance Conjugate Gradient benchmark as my test code, although we have received the same errors with other test codes. 
Problems with Intel MPI
By Palina L.3
I have trouble with running Intel MPI on cluster with different different numbers of processors on nodes (12 and 32). I use Intel MPI 4.0.3 and it works correctly on 20 nodes with 12 processors (Intel(Xeon(R)CPU X5650 @2.67)) at each, and all processors works correctly, then I try to run Intel MPI on other 3 nodes with 32 processors (Intel(Xeon(R)CPU E5-4620 v2@2.00) at each and they work correctly too. But when I try to run my tasks on all nodes with different types of processors and the same type of Intel MPI I cant use more than 48 processors. Spead falls. I use option --machinefile mpirun -machinefile mpihosts.txt ./wrf.exe mpihosts.txt (cn01:12 cn02:12 ... cn29:32 cn30:32) How can I use Intel MPI 4.0.3 correctly on all of these nodes?
Mapping ranks consecutively on nodes
By 4f0drlp7eyj34
Hi,    Running Intel MPI 4.1.3    Contrary to the user guide, which states for the default round-robin mapping, To change this default behavior, set the number of processes per host by using the -perhost option, and set the total number of processes by using the -n option. See Local Options for details. The first <# of processes> indicated by the -perhost option is executed on the first host; the next <# of processes> is executed on the next host, and so on. , when I try to run on 2 nodes and I_MPI_DEBUG=4, I see [cchang@n0290]$ mpirun -n 4 -perhost 2 ./hello_MPIMP_multinode [0] MPI startup(): Rank    Pid      Node name  Pin cpu [0] MPI startup(): 0       54622    n0290      {0,1,2,3,4,5,6,7,8,9,10,11} [0] MPI startup(): 1       53310    n0289      {0,1,2,3,4,5,6,7,8,9,10,11} [0] MPI startup(): 2       54623    n0290      {12,13,14,15,16,17,18,19,20,21,22,23} [0] MPI startup(): 3       53311    n0289      {12,13,14,15,16,17,18,19,20,21,22,23} Hello world: rank 0 o...
Intel MPI 5.0.3.048 Data Transmission Corruption Issue
By Stephen L.0
We are experiencing 3 failure modes with Intel MPI 5.0.3.048 on RHEL. Please change this to a private thread so that we can discuss details. Stephen Lecrenski
MPI: polling 'passive' rma operations
By zp34
Hi, lately I'm wondering if your implementation of the passive target communication was ever really ment for usage... Despite the fact that it isn't really passive (since one has to call some mpi functions on the target to get the mpi_win_unlock ever to return), I couldn't even figure out which mpi functions exactly must/can be invoked to achieve the flushing. In the release notes is only written: The following MPI-2.2 features are not supported by the Intel(R) MPI Library: o Passive target one-sided communication when  the target process does not call any MPI functions By now I've tested several 'MPI functions', but the only one that seems to work is a blocking MPI_RECV (and only then if the recv has to wait for the message). - Thats very unsatisfactory So my question: exist there at least some special functions that I can use for polling the rma window? I know this isn't foreseen of the mpi standard as less as your kind of implementation is, but it would render the whole thing a ...
Intel MPI, perhost, and SLURM: Can I override SLURM?
By thematt2
All, (Note: I'm also asking this on the slurm-dev list.) I'm hoping you can help me with a question. Namely, I'm on a cluster that uses SLURM and lets say I ask for 2 28-core Haswell nodes to run interactively and I get them. Great, so my environment now has things like: SLURM_NTASKS_PER_NODE=28 SLURM_TASKS_PER_NODE=28(x2) SLURM_JOB_CPUS_PER_NODE=28(x2) SLURM_CPUS_ON_NODE=28 Now, let's run a simple HelloWorld on, say, 48 processors (and pipe through sort to see things a bit better): (1047) $ mpirun -np 48 -print-rank-map ./helloWorld.exe | sort -k2 -g srun.slurm: cluster configuration lacks support for cpu binding (borgj102:0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27) (borgj105:28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47) Process 0 of 48 is on borgj102 Process 1 of 48 is on borgj102 Process 2 of 48 is on borgj102 Process 3 of 48 is on borgj102 Process 4 of 48 is on borgj102 Process 5 of 48 is on borgj102 Pro...
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  • 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.

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