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_simple
Note
You can change the name from spike_simple to the name of your target
This above command should generate a spike_simple folder with the following contents:
env # contains sample header file and linker file
riscof_spike_simple.py # sample spike plugin for RISCOF
spike_simple_isa.yaml # sample ISA YAML configuration file
spike_simple_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_simple
DUTPluginPath=/scratch/git-repo/incoresemi/riscof/spike_simple
[spike_simple]
pluginpath=/scratch/git-repo/incoresemi/riscof/spike_simple
ispec=/scratch/git-repo/incoresemi/riscof/spike_simple/spike_simple_isa.yaml
pspec=/scratch/git-repo/incoresemi/riscof/spike_simple/spike_simple_platform.yaml
The following changes need to be made:
Fix the paths in the
config.inito point to the folder containing the respective riscof_*.py files.The macros in the
spike_simple/env/compliance_model.hcan 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>.pywith respective functions as described in the following paragraphs.
The plugin file in the spike_simple folder: riscof_spike_simple.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 plugin. For e.g., in the default config.ini template the
pluginpath variable under the [spike_simple] header is available to the riscof_spike_simple.py
plugins by RISCOF. Similarly one can define more variables and prefixes here which can directly be
used in the plugins.
The idea here is to have a single place of change which is easy rather than hard-coding the same within the plugins.
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. 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 compliance 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.
compliance_env: This argument holds the absolute path of the directory where all the compliance 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, compliance_env):
if shutil.which('spike') is None:
logger.error('Please install spike to proceed further')
sys.exit(0)
self.work_dir = work_dir
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 ' + compliance_env
4.4.2. 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 to ability to tune themselves to a specific set of options 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 tool-chains.
The build function provides the following arguments:
isa_spec: This argument holds the path to the 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 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
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'
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.
4.4.3. 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' + parallel_jobs
for file in testList:
testentry = testList[file]
test = testentry['test_path']
test_dir = testentry['work_dir']
elf = 'my.elf'
execute = "cd "+testentry['work_dir']+";"
cmd = self.compile_cmd.format(testentry['isa'].lower(), self.xlen) + ' ' + test + ' -o ' + elf
compile_cmd = cmd + ' -D' + " -D".join(testentry['macros'])
execute+=compile_cmd+";"
sig_file = os.path.join(test_dir, self.name[:-1] + ".signature")
execute += spike_path + 'spike --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 colorlogger.info(<string>): Green colorlogger.error(<string>): Red color
Usage:
logger.debug('Performing Compile')