Getting Started
Prerequisites
Hatchet has the following minimum requirements, which must be installed before Hatchet is run:
Python 2 (2.7) or 3 (3.5 - 3.8)
matplotlib
pydot
numpy, and
pandas
Hatchet is available on GitHub.
Installation
You can get hatchet from its GitHub repository using this command:
$ git clone https://github.com/hatchet/hatchet.git
This will create a directory called hatchet
.
Install and Build Hatchet
To build hatchet and update your PYTHONPATH, run the following shell script from the hatchet root directory:
$ source ./install.sh
Note: The source
keyword is required to update your PYTHONPATH environment
variable. It is not necessary if you have already manually added the hatchet
directory to your PYTHONPATH.
Alternatively, you can install hatchet using pip:
$ pip install hatchet
Check Installation
After installing hatchet, you should be able to import hatchet when running the Python interpreter in interactive mode:
$ python
Python 3.7.4 (default, Jul 11 2019, 01:08:00)
[Clang 10.0.1 (clang-1001.0.46.4)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
Typing import hatchet
at the prompt should succeed without any error
messages:
>>> import hatchet
>>>
Supported data formats
Currently, hatchet supports the following data formats as input:
HPCToolkit database: This is generated by using
hpcprof-mpi
to post-process the raw measurements directory output by HPCToolkit.Caliper Cali file: This is the format in which caliper outputs raw performance data by default.
Caliper Json-split file: This is generated by either running cali-query on the raw caliper data or by enabling the mpireport service when using caliper.
DOT format: This is generated by using gprof2dot on
gprof
orcallgrind
output.String literal: Hatchet can read as input a list of dictionaries that represents a graph.
List: Hatchet can also read a list of lists that represents a graph.
For more details on the different input file formats, refer to the User Guide.