Go to file
yaozhicheng 32bafcfaf2 funcov: default return self & reset hinted 2024-11-08 10:42:14 +08:00
.github/workflows Add github workflow 2024-10-27 19:08:16 +08:00
example/adder Update testcase interface 2024-10-28 10:33:20 +08:00
scripts Add pre-commit-config and format code 2024-10-27 17:54:48 +08:00
tests Optimized import mode 2024-10-27 19:06:34 +08:00
toffee funcov: default return self & reset hinted 2024-11-08 10:42:14 +08:00
.gitignore Update pyproject and .gitignore 2024-10-27 18:10:17 +08:00
.pre-commit-config.yaml Add pre-commit-config and format code 2024-10-27 17:54:48 +08:00
LICENSE Add pre-commit-config and format code 2024-10-27 17:54:48 +08:00
README.md Add english README 2024-10-28 10:53:23 +08:00
README_zh.md Add english README 2024-10-28 10:53:23 +08:00
pyproject.toml Update pyproject.toml 2024-10-27 19:22:06 +08:00

README.md

Toffee

PyPI version

English Version | 中文版本

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.

Installation

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 .

Usage

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.

Additional Information

This project is part of UnityChip's open verification initiative. For more information, please visit open-verify.cc.