Instrument one section of code

The instrumentation scenarios are listed below, covering the most common situations.

Directory structure

So far you have the Linux kernel source tree and the PMUv3 plugin source code.

Next, create a third directory to learn how to integrate the PMUv3 plugin into an application as follows:

    

        
        
cd ../ ; mkdir test ; cd test

    

The instructions assume you have all three directories in parallel. If you have a different directory structure, you may need to adjust the build commands to find the header files and libraries.

Here are the 3 directories you now have:

    

        
        ./linux
./PMUv3_plugin
./test

        
    

You can use the test directory to try out the integration scenarios.

Instrumenting a single code block in C

The first scenario is to instrument a single section of code in C.

The general process to instrument code includes the following steps:

• Include 2 header files
• Initialize the plugin by calling pmuv3_bundle_init() with the bundle number as an argument
• Start counting by calling the function process_start_count()
• Call the function process_end_count() to stop counting
• Write the collected data to a CSV file by calling post_process() with the same bundle number
• Clean up with shutdown_resources()

As an example, use a text editor to create a file test1.c in the test directory with the contents below:

    

        
        
#include <stdio.h>
#include <stdint.h>
#include <math.h>

#include "pmuv3_plugin_bundle.h"
#include "processing.h"

#define VECTOR_SIZE 10000

void initialize_vectors(double vector_a[], double vector_b[], int size) {
    for (int i = 0; i < size; i++) {
        vector_a[i] = sin(i);
        vector_b[i] = cos(i);
    }
}

void calculate_result(double result[], double vector_a[], double vector_b[], int size) {
    for (int i = 0; i < size; i++) {
        result[i] = vector_a[i] + vector_b[i];
    }
}

int main(int argc, char **argv) {
    int bundle_number;
    struct CountData counter_data;

    /* Bundle number is passed as an argument */
    if (argc != 2) {
        fprintf(stderr, "Usage: %s <bundle number>\n", argv[0]);
        return EXIT_FAILURE;
    }
    bundle_number = atoi(argv[1]);

    /* Initialize the bundle of events */
    if (pmuv3_bundle_init(bundle_number) != 0) {
        fprintf(stderr, "Failed to initialize PMU bundle\n");
        return EXIT_FAILURE;
    }

    /* Code to be analyzed */
    process_start_count(&counter_data);

    /* Declare vectors */
    double vector_a[VECTOR_SIZE], vector_b[VECTOR_SIZE], result[VECTOR_SIZE];

    /* Initialize and calculate vectors */
    initialize_vectors(vector_a, vector_b, VECTOR_SIZE);
    calculate_result(result, vector_a, vector_b, VECTOR_SIZE);

    process_end_count(&counter_data);

    /* Write CSV file and clean up */
    post_process(bundle_number);
    shutdown_resources();

    return EXIT_SUCCESS;
}

    

The include files and function calls are added in the code to provide the performance instrumentation.

Build the application as follows:

    

        
        
gcc -I ../linux/tools/lib/perf/include  -I ../PMUv3_plugin/ test1.c -o test1 -L ../PMUv3_plugin/  -lpmuv3_plugin_bundle -lperf -lapi -lm

    

Run the application and pass the bundle number of 4 (to capture stall information):

    

        
        
sudo ./test1 4

    

The output prints the following:

    

        
        - running pmuv3_plugin_bundle.c...OK
End is 1404713, Start is 119346
End is 112270, Start is 43884
End is 285708, Start is 6714

        
    

The results are captured in the file bundle4.csv.

Display the text file to see the contents:

    

        
        
cat bundle4.csv

    

The data shows the metrics on the first line and the values on the second line as shown below:

    

        
        CPU_CYCLES,STALL_FRONTEND,STALL_BACKEND
1285367,68386,278994

        
    

Collect data for all bundles

You can quickly collect the data for all bundles. Save the code below in a file named run.sh:

    

        
        
#!/bin/bash

for i in {0..14}
do
  echo $i
  sudo ./test1 $i
done

    

Run the script:

    

        
        
bash ./run.sh

    

All 15 of the bundle CSV files have been generated.

Next, learn how you can visualize the data.