Skip to content

Measure Energy Consumption

The Intel Haswell nodes of ZIH system are equipped with power instrumentation that allow the recording and accounting of power dissipation and energy consumption data. The data is made available through several different interfaces, which are described below.

Summary of Measurement Interfaces

Interface Sensors Rate
Dataheap (C, Python, VampirTrace, Score-P) Blade, (CPU) 1 sample/s
HDEEM* (C, Score-P) Blade, CPU, DDR 1000 samples/s (Blade), 100 samples/s (VRs)
HDEEM Command Line Interface Blade, CPU, DDR 1000 samples/s (Blade), 100 samples/s (VR)
Slurm Accounting (sacct) Blade Per Job Energy
Slurm Profiling (HDF5) Blade Up to 1 sample/s


Please specify --partition=haswell --exclusive along with your job request if you wish to use HDEEM.

Accuracy, Temporal and Spatial Resolution

In addition to the above mentioned interfaces, you can access the measurements through a C API to get the full temporal and spatial resolution:

  • ** Blade:** 1000 samples/s for the whole node, includes both sockets, DRAM, SSD, and other on-board consumers. Since the system is directly water cooled, no cooling components are included in the blade consumption.
  • Voltage regulators (VR): 100 samples/s for each of the six VR measurement points, one for each socket and four for eight DRAM lanes (two lanes bundled).

The GPU blades also have 1 sample/s power instrumentation but have a lower accuracy.

HDEEM measurements have an accuracy of 2 % for Blade (node) measurements, and 5 % for voltage regulator (CPU, DDR) measurements.

Command Line Interface

The HDEEM infrastructure can be controlled through command line tools. They are commonly used on the node under test to start, stop, and query the measurement device.

  • startHdeem: Start a measurement. After the command succeeds, the measurement data with the 1000 / 100 samples/s described above will be recorded on the Board Management Controller (BMC), which is capable of storing up to 8h of measurement data.
  • stopHdeem: Stop a measurement. No further data is recorded and the previously recorded data remains available on the BMC.
  • printHdeem: Read the data from the BMC. By default, the data is written into a CSV file, whose name can be controlled using the -o argument.
  • checkHdeem: Print the status of the measurement device.
  • clearHdeem: Reset and clear the measurement device. No further data can be read from the device after this command is executed before a new measurement is started.


Please always execute clearHdeem before startHdeem.

Integration in Application Performance Traces

The per-node power consumption data can be included as metrics in application traces by using the provided metric plugins for Score-P (and VampirTrace). The plugins are provided as modules and set all necessary environment variables that are required to record data for all nodes that are part of the current job.

For 1 sample/s Blade values (Dataheap):

  • Score-P: use the module scorep-dataheap
  • VampirTrace: use the module vampirtrace-plugins/power-1.1 (Remark: VampirTrace is outdated!)

For 1000 samples/s (Blade) and 100 samples/s (CPU{0,1}, DDR{AB,CD,EF,GH}):

  • Score-P: use the module scorep-hdeem. This module requires a recent version of scorep/sync-.... Please use the latest that fits your compiler and MPI version.

By default, the modules are set up to record the power data for the nodes they are used on. For further information on how to change this behavior, please use module show on the respective module.

Example usage with gcc

marie@haswell$ module load scorep/trunk-2016-03-17-gcc-xmpi-cuda7.5
marie@haswell$ module load scorep-dataheap
marie@haswell$ scorep gcc application.c -o application
marie@haswell$ srun ./application

Once the application is finished, a trace will be available that allows you to correlate application functions with the component power consumption of the parallel application.


For energy measurements, only tracing is supported in Score-P/VampirTrace. The modules therefore disables profiling and enables tracing, please use Vampir to view the trace.

Energy measurements in Vampir

By default, scorep-dataheap records all sensors that are available. Currently this is the total node consumption and the CPUs. scorep-hdeem also records all available sensors (node, 2x CPU, 4x DDR) by default. You can change the selected sensors by setting the environment variables:


The power measurement modules scorep-dataheap and scorep-hdeem are dynamic and only need to be loaded during execution. However, scorep-hdeem does require the application to be linked with a certain version of Score-P.



For Dataheap

export SCOREP_METRIC_DATAHEAP_PLUGIN=localhost/watts

For more information on how to use Score-P, please refer to the respective documentation.

Access Using Slurm Tools

Slurm maintains its own database of job information, including energy data. There are two main ways of accessing this data, which are described below.

Post-Mortem Per-Job Accounting

This is the easiest way of accessing information about the energy consumed by a job and its job steps. The Slurm tool sacct allows users to query post-mortem energy data for any past job or job step by adding the field ConsumedEnergy to the --format parameter:

marie@login $ sacct --format="jobid,jobname,ntasks,submit,start,end,ConsumedEnergy,nodelist,state" -j 3967027
       JobID    JobName   NTasks              Submit               Start                 End ConsumedEnergy        NodeList      State
------------ ---------- -------- ------------------- ------------------- ------------------- -------------- --------------- ----------
3967027            bash          2014-01-07T12:25:42 2014-01-07T12:25:52 2014-01-07T12:41:20                    taurusi1159  COMPLETED
3967027.0         sleep        1 2014-01-07T12:26:07 2014-01-07T12:26:07 2014-01-07T12:26:18              0     taurusi1159  COMPLETED
3967027.1         sleep        1 2014-01-07T12:29:06 2014-01-07T12:29:06 2014-01-07T12:29:16          1.67K     taurusi1159  COMPLETED
3967027.2         sleep        1 2014-01-07T12:33:25 2014-01-07T12:33:25 2014-01-07T12:33:36          1.84K     taurusi1159  COMPLETED
3967027.3         sleep        1 2014-01-07T12:34:06 2014-01-07T12:34:06 2014-01-07T12:34:11          1.09K     taurusi1159  COMPLETED
3967027.4         sleep        1 2014-01-07T12:38:03 2014-01-07T12:38:03 2014-01-07T12:39:44         18.93K     taurusi1159  COMPLETED

This example job consisted of 5 job steps, each executing a sleep of a different length. Note that the ConsumedEnergy metric is only applicable to exclusive jobs.

Slurm Energy Profiling

The srun tool offers several options for profiling job steps by adding the --profile parameter. Possible profiling options are All, Energy, Task, Lustre, and Network. In all cases, the profiling information is stored in an HDF5 file that can be inspected using available HDF5 tools, e.g., h5dump. The files are stored under /scratch/profiling/ for each job, job step, and node. A description of the data fields in the file can be found in the official documentation. In general, the data files contain samples of the current power consumption on a per-second basis:

marie@login $ srun --partition haswell64 --acctg-freq=2,energy=1 --profile=energy sleep 10
srun: job 3967674 queued and waiting for resources
srun: job 3967674 has been allocated resources
marie@login $ h5dump /scratch/profiling/marie/3967674_0_taurusi1073.h5
  DATASET "Energy_0000000002 Data" {
      H5T_STRING {
        STRSIZE 24;
        CTYPE H5T_C_S1;
      } "Date_Time";
      H5T_STD_U64LE "Time";
      H5T_STD_U64LE "Power";
      H5T_STD_U64LE "CPU_Frequency";
    DATASPACE  SIMPLE { ( 1 ) / ( 1 ) }
    DATA {
    (0): {
        1389097545,  # timestamp
        174,         # power value

Using the HDEEM C API

Please specify --partition=haswell --exclusive along with your job request if you wish to use HDEEM.

Please download the official documentation at

The HDEEM header and sample code are locally installed on the nodes.

HDEEM header location


HDEEM sample location


Further Information and Citing

More information can be found in the paper HDEEM: high definition energy efficiency monitoring by Daniel Hackenberg et al. Please cite this paper if you are using HDEEM for your scientific work.