4. Create your Model Plugin¶

RISCOF requires python plugins for each model (DUT and Reference) to be submitted. These plugins provide a quick and standard way of building any model, compiling any/all the tests and executing the tests on the models.

4.1. Why Python Plugins ?¶

Since the entire RISCOF framework is in python it did not make sense to have the user-DUT in a separate environment. It would then cause issues in transferring data across these environments/domains.

While many prefer the conventional Makefile/autoconf approach, transferring the test-list in YAML to be used by another Makefile-environment seemed like a bad and an unscalable idea.

Expecting initial hesitation, we have tried to ensure that the python plugins can be made extremely simple (as crude as writing out bash instructions using shellCommand libraries).

Considering there would be a few backlashes in these choices, we have given enough pit-stops in the flow: validation, test-list, coverage, etc so one can stop at any point in the flow and move to their custom domain.

If you do feel the flow can be further improved or changed please do drop in an issue on the official repository.

4.2. Generate Templates¶

A sample template of the plugin and all other required collateral can be generated through RISCOF using the following command:

$ riscof setup --refname=sail_cSim --dutname=spike

Note

You can change the name from spike to the name of your target

This above command should generate a spike folder with the following contents:

env                                 # contains sample header file and linker file
riscof_spike.py              # sample spike plugin for RISCOF
spike_isa.yaml               # sample ISA YAML configuration file
spike_platform.yaml          # sample PLATFORM YAML configuration file

The command will also generate a sample config.ini file with the following contents:

[RISCOF]
ReferencePlugin=cSail
ReferencePluginPath=/scratch/git-repo/incoresemi/riscof/sail_cSim
DUTPlugin=spike
DUTPluginPath=/scratch/git-repo/incoresemi/riscof/spike

[spike]
pluginpath=/scratch/git-repo/incoresemi/riscof/spike
ispec=/scratch/git-repo/incoresemi/riscof/spike/spike_isa.yaml
pspec=/scratch/git-repo/incoresemi/riscof/spike/spike_platform.yaml

[sail_cSim]
pluginpath=/scratch/git-repo/incoresemi/riscof/sail_cSim

The following changes need to be made:

Fix the paths in the config.ini to point to the folder containing the respective riscof_*.py files.
The macros in the spike/env/model_test.h can be updated based on the model. Definitions of the macros and their use is available in the Test Format Spec.
Update the riscof_<target-name>.py with respective functions as described in the following paragraphs.

The plugin file in the spike folder: riscof_spike.py is the one that needs to be changed and updated for each model. As can be seen from this python file, it creates a Metaclass for the plugins supported by the abstract base class. This class basically offers the users three basic functions: initialize , build and runTests. For each model RISCOF calls these functions in the following order:

initialize --> build --> runTests

Please note the user is free to add more custom functions in this file which are called within the three base functions (as mentioned above).

4.3. Config.ini Syntax¶

The config.ini file generated using the above --setup command is used by RISCOF to locate the DUT and Reference plugins (along with their necessary collaterals). The config file also allows you to define specific nodes/fields which can be used by the respective model plugins. For e.g., in the default config.ini template the pluginpath variable under the [spike] header is available to the riscof_spike.py plugin via RISCOF. Similarly one can define more variables and prefixes here which can directly be used in the plugins.

For example, in the case of sail we can define a PATH variable which can point to where the C emulator binaries are located. This allows the plugin to directly probe which variable and use this as part of the execution commands.

The idea here is to have a single place of change which is easy rather than hard-coding the same within the plugins.

4.3.1. File path specification¶

Different values are allowed for the entries in config.ini to specify a path. They are checked in the following order, with the first found valid entry being used:

Absolute path: Usage of user home (~) is allowed.
Relative to current working directory: The path within the location where RISCOF was started.
Relative to config.ini location: A path staring from the point where config.ini is stored.

4.4. Function Definitions¶

We now define the various arguments and expected functionality of each of the above mentioned functions. Please note, this is not strict guide and the users can choose to perform different actions in different functions as opposed to what is outlined in this guide as long as they comply with the order of the functions being called and the signatures are generated in their respective directories at the end of the runTest function.

4.4.1. init (self, *args, **kwargs)¶

This is the constructor function for the pluginTemplate class. The configuration dictionary of the plugin, as specified in the config.ini, is passed to the plugin via the kwargs argument.

In this function you will also need to define the path of the model executable in the dut_exe variable as shown in line-6 below. Note, this variable can be dierctly set in the config.ini by setting the PATH variable under the model plugin’s header.

The num_jobs variable, in line-7, is used to indicate the number of parallel jobs that can be spawned for simulation.

Finally, thise constructor will capture the paths to the plugin, the isa yaml and the platform yaml for further usage (as seen in lines 13-14).

def __init__(self, *args, **kwargs):
    sclass = super().__init__(*args, **kwargs)

    config = kwargs.get('config')

    self.dut_exe = os.path.join(config['PATH'] if 'PATH' in config else "","spike")
    self.num_jobs = str(config['jobs'] if 'jobs' in config else 1)
    if config is None:
        print("Please enter input file paths in configuration.")
        raise SystemExit
    else:
        self.isa_spec = os.path.abspath(config['ispec'])
        self.platform_spec = os.path.abspath(config['pspec'])
        self.pluginpath=os.path.abspath(config['pluginpath'])

    return sclass

Warning

if the config is empty or if the isa and platform yamls are not available in the specified paths, the above function shall generate an error and exit.

4.4.2. initialize (suite, workdir, env)¶

This function is typically meant to create and initialize all necessary variables such as : compilation commands, elf2hex utility command, objdump command, include directories, etc. This function provides the following arguments which can be used:

suite: This argument holds the absolute path of the directory where the architectural test suite exists.This can be used to replace the name of the file to create directories in proper order.
workdir: This argument holds the absolute path of the work directory where all the execution and meta files/states will be dumped as part of running RISCOF.
archtest_env: This argument holds the absolute path of the directory where all the architectural test header files are located. This should be used to initialize the include arguments to the compiler/assembler.

An example of this function is shown below:

def initialise(self, suite, work_dir, archtest_env):
    if shutil.which(self.dut_exe) is None:
        logger.error(self.dut_exe+' Not Found')
        logger.error('Please install Executable for spike to proceed further')
        sys.exit(0)
    self.work_dir = work_dir

    #TODO: The following assumes you are using the riscv-gcc toolchain. If
    #      not please change appropriately
    self.compile_cmd = 'riscv{1}-unknown-elf-gcc -march={0} \
     -static -mcmodel=medany -fvisibility=hidden -nostdlib -nostartfiles\
     -T '+self.pluginpath+'/env/link.ld\
     -I '+self.pluginpath+'/env/\
     -I ' + archtest_env

    # set all the necessary variables like compile command, elf2hex
    # commands, objdump cmds. etc whichever you feel necessary and required
    # for your plugin.

The dut_exe variable in line-2 above, is derived and set in the __init__ function described earlier. This function checks if the dut_exe is indeed available and throws an error if not. The above template is used for the riscv-gnu-toolchain. If you are using an alternate or custom toolchain the compile_cmd, in line-10 above, will have to be changed appropriately.

One can also choose to add moer commands like objdump, elf2hex, etc from line 202 onwards which will be used further during the build and run phases.

4.4.3. build(isa_yaml, platform_yaml)¶

RISCOF is not limited to validating only a RTL targets, but can also be used to validate instruction set simulators (ISS) or modern day core-generators like rocket or chromite. These ISS and core generators have the ability to tune themselves to a specific set of configurations as defined in the standardized RISCV-CONFIG YAML. Thus, the build phase can be used as an intermediate stage to build or configure not only these models/targets but also be used to build respective custom tool-chains that may be required.

The build function provides the following arguments:

isa_spec: This argument holds the path to the validated ISA config YAML. This can be used to extract various fields from the YAML (e.g. ISA) and configure the DUT accordingly.
platform_spec: This argument holds the path to the validated PLATFORM config YAML and can be used similarly as above.

An example of this function for an ISS like spike is show below:

def build(self, isa_spec, platform_spec):
   ispec = utils.load_yaml(isa_yaml)['hart0']
   self.xlen = ('64' if 64 in ispec['supported_xlen'] else '32')
   self.isa = 'rv' + self.xlen
   #TODO: The following assumes you are using the riscv-gcc toolchain. If
   #      not please change appropriately
   self.compile_cmd = self.compile_cmd+' -mabi='+('lp64 ' if 64 in ispec['supported_xlen'] else 'ilp32 ')
   if "I" in ispec["ISA"]:
       self.isa += 'i'
   if "M" in ispec["ISA"]:
       self.isa += 'm'
   if "C" in ispec["ISA"]:
       self.isa += 'c'

   # based on the validated isa and platform configure your simulator or
   # build your RTL here

Note

For RTL targets this phase is typically empty and no actions are required. Though, one could choose to compile the RTL in this phase if required.

4.4.4. runTests(testlist)¶

This function is responsible for executing/running each test on the mode and produce individual signature files. A common approach is to create a simple Makefile with each test as a target using the commands and initializations done during the build and initialization phase. RISCOF also provides a simple makeUtil utility function which can be used directly, however, users are free to define their own execution environments. After generating the Makefile, the users should also call the make or suitable command to execute the run.

The function takes a single argument: testlist which is a dictionary of tests and respective meta informations. The format of the testlist is available here: Test List Format.

At the end of execution of this function it is expected that each test has a signature file available in the respective work_dir. The signature file generated should be named : self.name[:-1].+"signature"

A sample of this function which uses the shellCommand utility for compiling, executing and renaming the signature file. The function essentially iterates over all the tests in a sequence performing the same commands.

def runTests(self, testList):
    for file in testList:
        testentry = testList[file]
        test = testentry['test_path']
        test_dir = testentry['work_dir']

        elf = 'my.elf'
        sig_file = os.path.join(test_dir, self.name[:-1] + ".signature")

        cmd = self.compile_cmd.format(testentry['isa'].lower(), self.xlen) + ' ' + test + ' -o ' + elf
        compile_cmd = cmd + ' -D' + " -D".join(testentry['macros'])
        logger.debug('Compiling test: ' + test)
        utils.shellCommand(compile_cmd).run(cwd=test_dir)

        execute = spike_path + 'spike --isa={0} +signature={1} +signature-granularity=4 {2}'.format(self.isa, sig_file, elf)
        logger.debug('Executing on Spike ' + execute)
        utils.shellCommand(execute).run(cwd=test_dir)

An example which uses the makeUtil utility is show below. Here a Makefile is first generated where every test is a make target. the utility automatically creates the relevant targets and only requires the user to define what should occur under each target.

The user can choose to use a different make command by setting the make.makeCommand. More details of this utility are available at: Utils

def runTests(self, testList):
    make = utils.makeUtil(makefilePath=os.path.join(self.work_dir, "Makefile." + self.name[:-1]))
    make.makeCommand = 'make -j' + self.num_jobs
    for file in testList:
        testentry = testList[file]
        test = testentry['test_path']
        test_dir = testentry['work_dir']

        elf = 'dut.elf'

        execute = "@cd "+testentry['work_dir']+";"

        cmd = self.compile_cmd.format(testentry['isa'].lower(), self.xlen) + ' ' + test + ' -o ' + elf

        #TODO: we are using -D to enable compile time macros. If your
        #      toolchain is not riscv-gcc you may want to change the below code
        compile_cmd = cmd + ' -D' + " -D".join(testentry['macros'])
        execute+=compile_cmd+";"

        sig_file = os.path.join(test_dir, self.name[:-1] + ".signature")

        #TODO: You will need to add any other arguments to your DUT
        #      executable if any in the quotes below
        execute += self.dut_exe + ' --log-commits --log dump --isa={0} +signature={1} +signature-granularity=4 {2};'.format(self.isa, sig_file, elf)

        make.add_target(execute)
    make.execute_all(self.work_dir)

4.5. Other Utilities available¶

RISCOF also provides various standard and quick utilities that can be used by the plugins

4.5.1. logger¶

This utility is used for colored and prioritized printing on the terminal. It provides the following levels (in increasing order)

logger.debug(<string>): Blue color
logger.info(<string>): Green color
logger.error(<string>): Red color

Usage:

logger.debug('Performing Compile')

4.5.2. Other utilities¶

More utilities like makeUtil and shellcommand execution are available to the users. Details can be found here: Utils