mlvp has been renamed to Toffee
Toffee is a Python-based hardware verification framework designed to help users build hardware verification environments more conveniently and systematically using Python. It leverages the multi-language conversion tool picker, which converts Verilog code of hardware designs into Python Packages, enabling users to drive and verify hardware designs in Python.
Toffee incorporates elements of UVM methodology to ensure the verification environment's standardization and reusability. Moreover, Toffee redesigns the verification environment setup to better align with software developers' workflows, making it easier for software developers to engage in hardware verification tasks.
For more information about Toffee, please refer to the Toffee Documentation.
Toffee requires the following dependencies:
- Python 3.6.8+
- Picker 0.9.0+
Once these dependencies are installed, you can install Toffee via pip:
pip install pytoffee
Or install the latest version of Toffee with the following command:
pip install pytoffee@git+https://github.com/XS-MLVP/toffee@master
For a local installation:
git clone https://github.com/XS-MLVP/toffee.git
cd toffee
pip install .
We use a simple adder example located in the example/adder
directory to demonstrate how to use Toffee.
The design of the adder is as follows:
module Adder #(
parameter WIDTH = 64
) (
input [WIDTH-1:0] io_a,
input [WIDTH-1:0] io_b,
input io_cin,
output [WIDTH-1:0] io_sum,
output io_cout
);
assign {io_cout, io_sum} = io_a + io_b + io_cin;
endmodule
Before building the verification environment using Toffee, you need to use picker to convert the design into a Python Package. After installing the dependencies, run the following command in the example/adder
directory to complete the conversion:
make dut
To verify the functionality of the adder, you need to set up the verification environment using Toffee.
First, create a driver method for the adder interface. Here, Bundle
describes the interface to be driven, while Agent
is used to write the driving method for this interface. The setup is shown below:
class AdderBundle(Bundle):
a, b, cin, sum, cout = Signals(5)
class AdderAgent(Agent):
@driver_method()
async def exec_add(self, a, b, cin):
self.bundle.a.value = a
self.bundle.b.value = b
self.bundle.cin.value = cin
await self.bundle.step()
return self.bundle.sum.value, self.bundle.cout.value
To verify the functionality of the adder, define a Model
class to capture interaction information with the DUT and perform comparisons.
class AdderModel(Model):
@driver_hook(agent_name="add_agent")
def exec_add(self, a, b, cin):
result = a + b + cin
sum = result & ((1 << 64) - 1)
cout = result >> 64
return sum, cout
Next, create a top-level test environment and associate it with the Model, as shown below:
class AdderEnv(Env):
def __init__(self, adder_bundle):
super().__init__()
self.add_agent = AdderAgent(adder_bundle)
self.attach(AdderModel())
At this point, the verification environment is complete. The methods in the Model will be automatically invoked and compared with the output of the adder.
Afterward, write test cases to verify the functionality of the adder. With toffee-test, test cases can be written as follows:
@toffee_test.testcase
async def test_random(adder_env):
for _ in range(1000):
a = random.randint(0, 2**64 - 1)
b = random.randint(0, 2**64 - 1)
cin = random.randint(0, 1)
await adder_env.add_agent.exec_add(a, b, cin)
@toffee_test.testcase
async def test_boundary(adder_env):
for cin in [0, 1]:
for a in [0, 2**64 - 1]:
for b in [0, 2**64 - 1]:
await adder_env.add_agent.exec_add(a, b, cin)
Run the example in the example/adder
directory with the following command:
make run
A report will be automatically generated in the reports
directory upon completion.
For more detailed usage, please refer to the Toffee Documentation.
This project is part of UnityChip's open verification initiative. For more information, please visit open-verify.cc.