LLNL/Caliper

Name: Caliper

Owner: Lawrence Livermore National Laboratory

Description: Caliper is a flexible application introspection system

Created: 2015-11-11 02:02:00.0

Updated: 2018-03-28 16:07:49.0

Pushed: 2018-03-26 23:06:56.0

Homepage: null

Size: 4009

Language: C++

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README

Caliper: A Performance Analysis Toolbox in a Library

Build Status Coverage

Caliper is a program instrumentation and performance measurement framework. It is designed as a performance analysis toolbox in a library, allowing one to bake performance analysis capabilities directly into applications and activate them at runtime. Caliper is primarily aimed at HPC applications, but works for any C/C++/Fortran program on Unix/Linux.

Caliper's data collection mechanisms and source-code annotation API support a variety of performance engineering use cases, such as performance profiling, tracing, monitoring, and auto-tuning.

Features include:

Documentation

Extensive documentation is available here: https://llnl.github.io/Caliper/

Usage examples of the C++ and C annotation interfaces are provided in the examples/apps directory.

See the “Getting started” section below for a brief tutorial.

Example applications, configuration files, and a more extensive tutorial can be found here: https://github.com/LLNL/caliper-examples

Building and installing

Building and installing Caliper requires cmake 3.1+ and a current C++11-compatible Compiler. Clone Caliper from github and proceed as follows:

 $ git clone https://github.com/LLNL/Caliper.git
 $ cd Caliper
 $ mkdir build && cd build
 $ cmake -DCMAKE_INSTALL_PREFIX=<path to install location> \
     -DCMAKE_C_COMPILER=<path to c-compiler> \
     -DCMAKE_CXX_COMPILER=<path to c++-compiler> \
     ..
 $ make
 $ make install

See the “Build and install” section in the documentation for further information.

Getting started

Typically, we integrate Caliper into a program by marking source-code sections of interest with descriptive annotations. Performance measurements, trace or profile collection, and reporting functionality can then be enabled with runtime configuration options. Alternatively, third-party tools can connect to Caliper and access information provided by the source-code annotations.

Source-code annotations

Caliper's source-code annotation API fulfills two purposes: First, it lets us associate performance measurements with user-defined, high-level context information. Second, we can trigger user-defined actions at the instrumentation points, e.g. to measure the time spent in individual regions. Measurement actions can be defined at runtime and are disabled by default; generally, the source-code annotations are lightweight enough to be left in production code.

The annotation APIs are available for C, C++, and Fortran. There are high-level annotation macros for common scenarios such as marking functions, loops, or sections of source-code. In addition, users can export arbitrary key:value pairs to express application-specific concepts.

The following example marks “initialization” and “main loop” phases in a C++ code, and exports the main loop's current iteration counter using the high-level annotation macros:

lude <caliper/cali.h>

main(int argc, char* argv[])

// Mark this function
CALI_CXX_MARK_FUNCTION;

// Mark the "intialization" phase
CALI_MARK_BEGIN("initialization");
int count = 4;
double t = 0.0, delta_t = 1e-6;
CALI_MARK_END("initialization");

// Mark the loop
CALI_CXX_MARK_LOOP_BEGIN(mainloop, "main loop");

for (int i = 0; i < count; ++i) {
    // Mark each loop iteration
    CALI_CXX_MARK_LOOP_ITERATION(mainloop, i);

    // A Caliper snapshot taken at this point will contain
    // { "function"="main", "loop"="main loop", "iteration#main loop"=<i> }

    // ...
}

CALI_CXX_MARK_LOOP_END(mainloop);

Linking the Caliper library

To use Caliper, add annotation statements to your program and link it against the Caliper library. Programs must be linked with the Caliper runtime (libcaliper.so), as shown in the example link command:

g++ -o app app.o -L<path to caliper installation>/lib64 -lcaliper
Runtime configuration

Caliper's performance measurement and data collection functionality must be enabled and configured at runtime through Caliper's configuration API, configuration files, or environment variables. By default, Caliper will keep track of the current Caliper context provided by the annotation API calls (allowing third-party tools to access program context information), but won't run any performance measurement or data recording on its own.

Generally, collecting performance data with Caliper requires selecting a combination of Caliper services that implement specific functionality and configuring them for the task at hand. However, for some common scenarios, Caliper provides a set of pre-defined configuration profiles. These profiles can be activated with the CALI_CONFIG_PROFILE environment variable. For example, the runtime-report configuration profile prints the total time (in microseconds) spent in each code path based on the nesting of annotated code regions:

$ CALI_CONFIG_PROFILE=runtime-report ./examples/apps/cali-basic-annotations
Path          sum#time.duration
main                  20.000000
  main loop            8.000000
  init                10.000000

The example shows Caliper output for the runtime-report configuration profile for the source-code annotation example above.

As another example, the serial-trace configuration profile configures Caliper to record an event trace of each annotation event:

$ CALI_CONFIG_PROFILE=serial-trace ./examples/apps/cali-basic-annotations
== CALIPER: Registered event trigger service
== CALIPER: Registered recorder service
== CALIPER: Registered timestamp service
== CALIPER: Registered trace service
== CALIPER: Initialized
== CALIPER: Flushing Caliper data
== CALIPER: Trace: Flushed 14 snapshots.
== CALIPER: Recorder: Wrote 71 records.

The trace data is stored in a .cali file in a text-based Caliper-specific file format. Use the cali-query tool to filter, aggregate, or print the recorded data. Here, we use cali-query to print the recorded trace data in a human-readable json format:

$ ls *.cali
171120-181836_40337_7LOlCN5RchWV.cali
$ cali-query 171120-181836_40337_7LOlCN5RchWV.cali -q "SELECT * FORMAT json(pretty)"
[
{
        "event.begin#function":"main"
},
{
        "event.begin#annotation":"init",
        "function":"main"
},
{
        "event.end#annotation":"init",
        "annotation":"init",
        "function":"main",
        "time.inclusive.duration":14
},
{
        "event.begin#loop":"main loop",
        "function":"main"
},
{
        "loop":"main loop",
        "function":"main",
        "event.begin#iteration#main loop":0
},
...

As mentioned earlier, Caliper's performance measurement and data collection functionality is provided by independent building blocks called services, each implementing specific functionality (e.g., tracing, I/O, timing, report formatting, sampling, etc.). The services can be enabled at runtime in any combination. This makes Caliper highly flexible, but the runtime configuration can be complex. Refer to the Caliper documentation to learn more.

Authors

Caliper was created by David Boehme, boehme3@llnl.gov.

A complete list of contributors is available on GitHub.

Major contributors include:

Citing Caliper

To reference Caliper in a publication, please cite the following paper:

Release

Caliper is released under a BSD license. See the LICENSE file for details.

LLNL-CODE-678900


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.