Skip to content

PAPI

Introduction

Performance Application Programming Interface (PAPI) is a portable interface to access hardware performance counters (such as instruction counts and cache misses) found in most modern architectures. With the new component framework, PAPI is not limited only to CPU counters, but offers also components for CUDA, network, Infiniband, etc.

PAPI provides two levels of interface: a simpler high-level interface and more detailed low-level interface.

PAPI can be used with parallel as well as serial programs.

Installed Versions

For the current list of installed versions, use:

$ ml av papi

Utilities

The bin directory of PAPI, which is automatically added to $PATH upon loading the module, contains various utilites.

Papi_avail

Prints which preset events are available on the current CPU. The third column indicates whether the preset event is available on the current CPU.

  • Barbora cluster
$ papi_avail
Available PAPI preset and user defined events plus hardware information.
--------------------------------------------------------------------------------
PAPI version             : 6.0.0.0
Operating system         : Linux 3.10.0-1160.6.1.el7.x86_64
Vendor string and code   : GenuineIntel (1, 0x1)
Model string and code    : Intel(R) Xeon(R) Gold 6240 CPU @ 2.60GHz (85, 0x55)
CPU revision             : 7.000000
CPUID                    : Family/Model/Stepping 6/85/7, 0x06/0x55/0x07
CPU Max MHz              : 3900
CPU Min MHz              : 1000
Total cores              : 72
SMT threads per core     : 2
Cores per socket         : 18
Sockets                  : 2
Cores per NUMA region    : 36
NUMA regions             : 2
Running in a VM          : no
Number Hardware Counters : 10
Max Multiplex Counters   : 384
Fast counter read (rdpmc): no
--------------------------------------------------------------------------------

================================================================================
  PAPI Preset Events
================================================================================
    Name        Code    Avail Deriv Description (Note)
PAPI_L1_DCM  0x80000000  Yes   No   Level 1 data cache misses
PAPI_L1_ICM  0x80000001  Yes   No   Level 1 instruction cache misses
PAPI_L2_DCM  0x80000002  Yes   Yes  Level 2 data cache misses
PAPI_L2_ICM  0x80000003  Yes   No   Level 2 instruction cache misses
PAPI_L3_DCM  0x80000004  No    No   Level 3 data cache misses
PAPI_L3_ICM  0x80000005  No    No   Level 3 instruction cache misses
PAPI_L1_TCM  0x80000006  Yes   Yes  Level 1 cache misses
PAPI_L2_TCM  0x80000007  Yes   No   Level 2 cache misses
PAPI_L3_TCM  0x80000008  Yes   No   Level 3 cache misses
    ....
  • Karolina cluster
Available PAPI preset and user defined events plus hardware information.
--------------------------------------------------------------------------------
PAPI version             : 6.0.0.0
Operating system         : Linux 3.10.0-1160.21.1.el7.x86_64
Vendor string and code   : AuthenticAMD (2, 0x2)
Model string and code    : AMD EPYC 7H12 64-Core Processor (49, 0x31)
CPU revision             : 0.000000
CPUID                    : Family/Model/Stepping 23/49/0, 0x17/0x31/0x00
CPU Max MHz              : 2594
CPU Min MHz              : 2594
Total cores              : 128
SMT threads per core     : 1
Cores per socket         : 64
Sockets                  : 2
Cores per NUMA region    : 16
NUMA regions             : 8
Running in a VM          : no
Number Hardware Counters : 5
Max Multiplex Counters   : 384
Fast counter read (rdpmc): no
--------------------------------------------------------------------------------

================================================================================
  PAPI Preset Events
================================================================================
    Name        Code    Avail Deriv Description (Note)
PAPI_L1_DCM  0x80000000  No    No   Level 1 data cache misses
PAPI_L1_ICM  0x80000001  No    No   Level 1 instruction cache misses
PAPI_L2_DCM  0x80000002  No    No   Level 2 data cache misses
PAPI_L2_ICM  0x80000003  No    No   Level 2 instruction cache misses
PAPI_L3_DCM  0x80000004  No    No   Level 3 data cache misses
PAPI_L3_ICM  0x80000005  No    No   Level 3 instruction cache misses
PAPI_L1_TCM  0x80000006  No    No   Level 1 cache misses
PAPI_L2_TCM  0x80000007  No    No   Level 2 cache misses
PAPI_L3_TCM  0x80000008  No    No   Level 3 cache misses
...

Papi_native_avail

Prints which native events are available on the current CPU.

Papi_cost

Measures the cost (in cycles) of basic PAPI operations.

Papi_mem_info

Prints information about the memory architecture of the current CPU.

PAPI API

PAPI provides two kinds of events:

  • Preset events is a set of predefined common CPU events, standardized across platforms.
  • Native events is a set of all events supported by the current hardware. This is a larger set of features than preset. For other components than CPU, only native events are usually available.

To use PAPI in your application, you need to link the appropriate include file.

  • papi.h for C
  • f77papi.h for Fortran 77
  • f90papi.h for Fortran 90
  • fpapi.h for Fortran with preprocessor

The include path is automatically added by the papi module to $INCLUDE.

High-Level API

Refer to this description of the High-level API.

Low-Level API

Please refer to this description of the Low-level API.

Timers

PAPI provides the most accurate timers the platform can support, see.

System Information

PAPI can be used to query some system information, such as CPU name and MHz, see.

Example

The following example prints MFLOPS rate of a naive matrix-matrix multiplication:

    #include <stdlib.h>
    #include <stdio.h>
    #include "papi.h"
    #define SIZE 1000

    int main(int argc, char **argv) {
     float matrixa[SIZE][SIZE], matrixb[SIZE][SIZE], mresult[SIZE][SIZE];
     float real_time, proc_time, mflops;
     long long flpins;
     int retval;
     int i,j,k;

     /* Initialize the Matrix arrays */
     for ( i=0; i<SIZE*SIZE; i++ ){
     mresult[0][i] = 0.0;
     matrixa[0][i] = matrixb[0][i] = rand()*(float)1.1;
     }

     /* Setup PAPI library and begin collecting data from the counters */
     if((retval=PAPI_flops( &real_time, &proc_time, &flpins, &mflops))<PAPI_OK)
     printf("Error!");

     /* A naive Matrix-Matrix multiplication */
     for (i=0;i<SIZE;i++)
     for(j=0;j<SIZE;j++)
     for(k=0;k<SIZE;k++)
     mresult[i][j]=mresult[i][j] + matrixa[i][k]*matrixb[k][j];

     /* Collect the data into the variables passed in */
     if((retval=PAPI_flops( &real_time, &proc_time, &flpins, &mflops))<PAPI_OK)
     printf("Error!");

     printf("Real_time:t%fnProc_time:t%fnTotal flpins:t%lldnMFLOPS:tt%fn", real_time, proc_time, flpins, mflops);
     PAPI_shutdown();
     return 0;
    }

Now compile and run the example:

$ gcc matrix.c -o matrix -lpapi
$ ./matrix
    Real_time: 8.852785
    Proc_time: 8.850000
    Total flpins: 6012390908
    MFLOPS: 679.366211

Let us try with optimizations enabled:

$ gcc -O3 matrix.c -o matrix -lpapi
$ ./matrix
    Real_time: 0.000020
    Proc_time: 0.000000
    Total flpins: 6
    MFLOPS: inf

Now we see a seemingly strange result - the multiplication took no time and only 6 floating point instructions were issued. This is because the compiler optimizations have completely removed the multiplication loop, as the result is actually not used anywhere in the program. We can fix this by adding some "dummy" code at the end of the Matrix-Matrix multiplication routine:

    for (i=0; i<SIZE;i++)
     for (j=0; j<SIZE; j++)
       if (mresult[i][j] == -1.0) printf("x");

Now the compiler will not remove the multiplication loop. (However, it is still not that smart to see that the result will never be negative). Now run the code again:

$ gcc -O3 matrix.c -o matrix -lpapi
$ ./matrix
    Real_time: 8.795956
    Proc_time: 8.790000
    Total flpins: 18700983160
    MFLOPS: 2127.529297

References

  1. Main project page
  2. Wiki
  3. API Documentation

Comments