Quickstart Guide

Installing cocotb


Cocotb has the following requirements:

  • Python 2.7+

  • Python-dev packages

  • GCC and associated development packages

  • GNU Make

  • A Verilog or VHDL simulator, depending on your source RTL code

Internal development is performed on Linux Mint 17 (x64). We also use RedHat 6.5(x64). Other RedHat and Ubuntu based distributions (x32 and x64) should work too but due fragmented nature of Linux we can not test everything. Instructions are provided for the main distributions we use.

Linux native arch installation

Ubuntu based installation

$> sudo apt-get install git make gcc g++ swig python-dev

This will allow building of the cocotb libs for use with a 64-bit native simulator. If a 32-bit simulator is being used then additional steps to install 32-bit development libraries and Python are needed.

RedHat based installation

$> sudo yum install gcc gcc-c++ libstdc++-devel swig python-devel

This will allow building of the cocotb libs for use with a 64-bit native simulator. If a 32-bit simulator is being used then additional steps to install 32-bit development libraries and Python are needed.

32-bit Python

Additional development libraries are needed for building 32-bit Python on 64-bit systems.

Ubuntu based installation

$> sudo apt-get install libx32gcc1 gcc-4.8-multilib lib32stdc++-4.8-dev

Replace 4.8 with the version of GCC that was installed on the system in the step above. Unlike on RedHat where 32-bit Python can co-exist with native Python, Ubuntu requires the source to be downloaded and built.

RedHat based installation

$> sudo yum install glibc.i686 glibc-devel.i386 libgcc.i686 libstdc++-devel.i686

Specific releases can be downloaded from https://www.python.org/downloads/ .

$> wget https://www.python.org/ftp/python/2.7.9/Python-2.7.9.tgz
$> tar xvf Python-2.7.9.tgz
$> cd Python-2.7.9
$> export PY32_DIR=/opt/pym32
$> ./configure CC="gcc -m32" LDFLAGS="-L/lib32 -L/usr/lib32 -Lpwd/lib32 -Wl,-rpath,/lib32 -Wl,-rpath,$PY32_DIR/lib" --prefix=$PY32_DIR --enable-shared
$> make
$> sudo make install

Cocotb can now be built against 32-bit Python by setting the architecture and placing the 32-bit Python ahead of the native version in the path when running a test.

$> export PATH=/opt/pym32/bin
$> cd <cocotb_dir>
$> ARCH=i686 make

Windows 7 installation

Work has been done with the support of the cocotb community to enable Windows support using the MinGW/Msys environment. Download the MinGQ installer from.

https://sourceforge.net/projects/mingw/files/latest/download?source=files .

Run the GUI installer and specify a directory you would like the environment installed in. The installer will retrieve a list of possible packages, when this is done press continue. The MinGW Installation Manager is then launched.

The following packages need selecting by checking the tick box and selecting “Mark for installation”

Basic Installation
  -- mingw-developer-tools
  -- mingw32-base
  -- mingw32-gcc-g++
  -- msys-base

From the Installation menu then select “Apply Changes”, in the next dialog select “Apply”.

When installed a shell can be opened using the “msys.bat” file located under the <install_dir>/msys/1.0/

Python can be downloaded from https://www.python.org/ftp/python/2.7.9/python-2.7.9.msi, other versions of Python can be used as well. Run the installer and download to your chosen location.

It is beneficial to add the path to Python to the Windows system PATH variable so it can be used easily from inside Msys.

Once inside the Msys shell commands as given here will work as expected.

macOS Packages

You need a few packages installed to get cocotb running on macOS. Installing a package manager really helps things out here.

Brew seems to be the most popular, so we’ll assume you have that installed.

$> brew install python icarus-verilog gtkwave

Installing cocotb

Cocotb can be installed by running (recommended Python3)

$> pip3 install cocotb


$> pip install cocotb

*For user local install follow pip User Guide.

For development version:

$> git clone https://github.com/cocotb/cocotb
$> pip install -e ./cocotb

Running an example

$> git clone https://github.com/cocotb/cocotb
$> cd cocotb/examples/endian_swapper/tests
$> make

To run a test using a different simulator:

$> make SIM=vcs

Running a VHDL example

The endian_swapper example includes both a VHDL and a Verilog RTL implementation. The cocotb testbench can execute against either implementation using VPI for Verilog and VHPI/FLI for VHDL. To run the test suite against the VHDL implementation use the following command (a VHPI or FLI capable simulator must be used):

$> make SIM=ghdl TOPLEVEL_LANG=vhdl

Using cocotb

A typical cocotb testbench requires no additional RTL code. The Design Under Test (DUT) is instantiated as the toplevel in the simulator without any wrapper code. Cocotb drives stimulus onto the inputs to the DUT and monitors the outputs directly from Python.

Creating a Makefile

To create a cocotb test we typically have to create a Makefile. Cocotb provides rules which make it easy to get started. We simply inform cocotb of the source files we need compiling, the toplevel entity to instantiate and the Python test script to load.

VERILOG_SOURCES = $(PWD)/submodule.sv $(PWD)/my_design.sv
TOPLEVEL=my_design  # the module name in your Verilog or VHDL file
MODULE=test_my_design  # the name of the Python test file
include $(shell cocotb-config --makefiles)/Makefile.inc
include $(shell cocotb-config --makefiles)/Makefile.sim

We would then create a file called test_my_design.py containing our tests.

Creating a test

The test is written in Python. Cocotb wraps your top level with the handle you pass it. In this documentation, and most of the examples in the project, that handle is dut, but you can pass your own preferred name in instead. The handle is used in all Python files referencing your RTL project. Assuming we have a toplevel port called clk we could create a test file containing the following:

import cocotb
from cocotb.triggers import Timer

def my_first_test(dut):
    """Try accessing the design."""

    dut._log.info("Running test!")
    for cycle in range(10):
        dut.clk = 0
        yield Timer(1000)
        dut.clk = 1
        yield Timer(1000)
    dut._log.info("Running test!")

This will drive a square wave clock onto the clk port of the toplevel.

Accessing the design

When cocotb initialises it finds the top-level instantiation in the simulator and creates a handle called dut. Top-level signals can be accessed using the “dot” notation used for accessing object attributes in Python. The same mechanism can be used to access signals inside the design.

# Get a reference to the "clk" signal on the top-level
clk = dut.clk

# Get a reference to a register "count"
# in a sub-block "inst_sub_block"
count = dut.inst_sub_block.count

Assigning values to signals

Values can be assigned to signals using either the value property of a handle object or using direct assignment while traversing the hierarchy.

# Get a reference to the "clk" signal and assign a value
clk = dut.clk
clk.value = 1

# Direct assignment through the hierarchy
dut.input_signal <= 12

# Assign a value to a memory deep in the hierarchy
dut.sub_block.memory.array[4] <= 2

The syntax sig <= new_value is a short form of sig.value = new_value. It not only resembles HDL-syntax, but also has the same semantics: writes are not applied immediately, but delayed until the next write cycle. Use sig.setimmediatevalue(new_val) to set a new value immediately (see setimmediatevalue()).

Reading values from signals

Accessing the value property of a handle object will return a BinaryValue object. Any unresolved bits are preserved and can be accessed using the binstr attribute, or a resolved integer value can be accessed using the integer attribute.

>>> # Read a value back from the DUT
>>> count = dut.counter.value
>>> print(count.binstr)
>>> # Resolve the value to an integer (X or Z treated as 0)
>>> print(count.integer)
>>> # Show number of bits in a value
>>> print(count.n_bits)

We can also cast the signal handle directly to an integer:

>>> print(int(dut.counter))

Parallel and sequential execution of coroutines

def reset_dut(reset_n, duration):
    reset_n <= 0
    yield Timer(duration)
    reset_n <= 1
    reset_n._log.debug("Reset complete")

def parallel_example(dut):
    reset_n = dut.reset

    # This will call reset_dut sequentially
    # Execution will block until reset_dut has completed
    yield reset_dut(reset_n, 500)
    dut._log.debug("After reset")

    # Call reset_dut in parallel with this coroutine
    reset_thread = cocotb.fork(reset_dut(reset_n, 500)

    yield Timer(250)
    dut._log.debug("During reset (reset_n = %s)" % reset_n.value)

    # Wait for the other thread to complete
    yield reset_thread.join()
    dut._log.debug("After reset")