This tutorial demonstrates how to validate 224G Ethernet interfaces using the SerDes Validation Framework, focusing on:
- Equipment setup and configuration
- Link training validation
- Compliance testing
- Performance analysis
from typing import Dict, List, Optional, Union
import numpy as np
import numpy.typing as npt
from serdes_validation_framework.instrument_control.scope_224g import (
HighBandwidthScope,
ScopeConfig
)
def configure_validation_setup(
scope_address: str,
sample_rate: float = 256e9,
bandwidth: float = 120e9
) -> HighBandwidthScope:
"""
Configure scope for 224G validation with type checking
Args:
scope_address: VISA resource identifier
sample_rate: Sample rate in Hz
bandwidth: Bandwidth in Hz
Returns:
Configured scope instance
Raises:
AssertionError: If parameters are invalid
ConnectionError: If setup fails
"""
# Validate inputs
assert isinstance(scope_address, str), "Scope address must be string"
assert isinstance(sample_rate, float), "Sample rate must be float"
assert isinstance(bandwidth, float), "Bandwidth must be float"
assert sample_rate > 0, "Sample rate must be positive"
assert bandwidth > 0, "Bandwidth must be positive"
# Create configuration
config = ScopeConfig(
sampling_rate=sample_rate,
bandwidth=bandwidth,
timebase=5e-12, # 5 ps/div
voltage_range=0.8 # 0.8V
)
try:
# Initialize scope
scope = HighBandwidthScope(scope_address)
scope.configure_for_224g(config)
return scope
except Exception as e:
raise ConnectionError(f"Failed to configure scope: {e}")def validate_waveform_data(
time_data: npt.NDArray[np.float64],
voltage_data: npt.NDArray[np.float64]
) -> None:
"""
Validate waveform data arrays
Args:
time_data: Time points array
voltage_data: Voltage measurements array
Raises:
AssertionError: If validation fails
"""
# Type validation
assert isinstance(time_data, np.ndarray), \
f"Time data must be numpy array, got {type(time_data)}"
assert isinstance(voltage_data, np.ndarray), \
f"Voltage data must be numpy array, got {type(voltage_data)}"
# Data type validation
assert np.issubdtype(time_data.dtype, np.floating), \
f"Time data must be floating-point, got {time_data.dtype}"
assert np.issubdtype(voltage_data.dtype, np.floating), \
f"Voltage data must be floating-point, got {voltage_data.dtype}"
# Array validation
assert len(time_data) == len(voltage_data), \
f"Array length mismatch: {len(time_data)} != {len(voltage_data)}"
assert len(time_data) > 0, "Arrays cannot be empty"
# Value validation
assert not np.any(np.isnan(time_data)), "Time data contains NaN values"
assert not np.any(np.isnan(voltage_data)), "Voltage data contains NaN values"
assert not np.any(np.isinf(time_data)), "Time data contains infinite values"
assert not np.any(np.isinf(voltage_data)), "Voltage data contains infinite values"from serdes_validation_framework.protocols.ethernet_224g.training import (
EqualizerConfig,
EnhancedEqualizer
)
def setup_link_training(
adaptation_rate: float = 0.01,
max_iterations: int = 1000
) -> EnhancedEqualizer:
"""
Configure link training parameters
Args:
adaptation_rate: Equalizer adaptation rate
max_iterations: Maximum training iterations
Returns:
Configured equalizer instance
"""
# Validate inputs
assert isinstance(adaptation_rate, float), \
"Adaptation rate must be float"
assert isinstance(max_iterations, int), \
"Max iterations must be integer"
assert 0 < adaptation_rate < 1, \
"Adaptation rate must be between 0 and 1"
assert max_iterations > 0, \
"Max iterations must be positive"
# Create configuration
config = EqualizerConfig(
fir_taps=11, # Odd number for symmetric FIR
dfe_taps=3, # Typical for 224G
adaptation_rate=adaptation_rate,
max_iterations=max_iterations,
convergence_threshold=1e-6,
min_snr=20.0,
algorithm='lms'
)
return EnhancedEqualizer(config)def run_link_training(
scope: HighBandwidthScope,
equalizer: EnhancedEqualizer,
duration: float = 1e-6
) -> Dict[str, Union[float, List[float]]]:
"""
Run link training sequence
Args:
scope: Configured scope instance
equalizer: Configured equalizer
duration: Training duration in seconds
Returns:
Dictionary of training results
"""
# Validate inputs
assert isinstance(duration, float), "Duration must be float"
assert duration > 0, "Duration must be positive"
try:
# Capture training data
waveform = scope.capture_waveform(
duration=duration,
sample_rate=scope.config.sampling_rate
)
# Validate captured data
validate_waveform_data(waveform.time, waveform.voltage)
# Run training
trained_signal, state = equalizer.train(
waveform.voltage,
np.roll(waveform.voltage, -1) # Simple target
)
# Return results
return {
'training_time': float(duration),
'convergence_status': state.error_history[-1] < equalizer.config.convergence_threshold,
'final_error': float(state.error_history[-1]),
'tap_weights': list(map(float, state.fir_taps))
}
except Exception as e:
raise RuntimeError(f"Link training failed: {e}")from serdes_validation_framework.protocols.ethernet_224g.compliance import (
ComplianceSpecification,
ComplianceTestConfig
)
def setup_compliance_tests() -> Tuple[ComplianceSpecification, Dict[str, float]]:
"""
Set up compliance testing configuration
Returns:
Tuple of (ComplianceSpecification, test limits)
"""
# Create specification checker
spec = ComplianceSpecification()
# Define test limits
limits = {
'eye_height_min': 0.2, # Minimum eye height
'eye_width_min': 0.4, # Minimum eye width
'rms_evm_max': 5.0, # Maximum RMS EVM percentage
'jitter_max': 0.3e-12 # Maximum total jitter
}
return spec, limitsdef run_compliance_tests(
scope: HighBandwidthScope,
spec: ComplianceSpecification,
limits: Dict[str, float]
) -> Dict[str, Dict[str, float]]:
"""
Run compliance test suite
Args:
scope: Configured scope instance
spec: Compliance specification
limits: Test limits
Returns:
Dictionary of test results
"""
try:
results = {}
# Level compliance
levels = scope.measure_pam4_levels()
level_status, level_measurements = spec.check_pam4_levels(
levels.level_means
)
results['levels'] = level_measurements
# Eye diagram
eye = scope.capture_eye_diagram()
eye_status, eye_measurements = spec.check_eye_diagram(
eye.worst_eye_height,
eye.worst_eye_width
)
results['eye'] = eye_measurements
# Jitter
jitter = scope.measure_jitter()
results['jitter'] = jitter
# Overall status
results['status'] = all([
level_status,
eye_status,
jitter['tj'] < limits['jitter_max']
])
return results
except Exception as e:
raise RuntimeError(f"Compliance testing failed: {e}")def run_validation_sequence() -> None:
"""Run complete 224G validation sequence"""
# Force mock mode for example
os.environ['SVF_MOCK_MODE'] = '1'
try:
# 1. Setup equipment
scope = configure_validation_setup('GPIB0::7::INSTR')
# 2. Run link training
equalizer = setup_link_training()
training_results = run_link_training(scope, equalizer)
print("\nLink Training Results:")
print(f"Status: {'Converged' if training_results['convergence_status'] else 'Failed'}")
print(f"Final Error: {training_results['final_error']:.6f}")
# 3. Run compliance tests
spec, limits = setup_compliance_tests()
compliance_results = run_compliance_tests(scope, spec, limits)
print("\nCompliance Test Results:")
print(f"Overall Status: {'PASS' if compliance_results['status'] else 'FAIL'}")
print("\nDetailed Measurements:")
for category, measurements in compliance_results.items():
if category != 'status':
print(f"\n{category.upper()}:")
for param, value in measurements.items():
print(f" {param}: {value}")
except Exception as e:
print(f"Validation failed: {e}")
finally:
# Cleanup
scope.cleanup()Always validate numeric inputs:
def validate_numeric_parameter(
value: float,
name: str,
min_value: Optional[float] = None,
max_value: Optional[float] = None
) -> None:
"""Validate numeric parameter"""
assert isinstance(value, float), \
f"{name} must be float, got {type(value)}"
if min_value is not None:
assert value >= min_value, \
f"{name} must be >= {min_value}"
if max_value is not None:
assert value <= max_value, \
f"{name} must be <= {max_value}"Use proper error hierarchy:
class ValidationError(Exception):
"""Base validation error"""
pass
class ConfigError(ValidationError):
"""Configuration error"""
pass
class MeasurementError(ValidationError):
"""Measurement error"""
passValidate measurement results:
def validate_results(
results: Dict[str, Dict[str, float]],
limits: Dict[str, float]
) -> bool:
"""Validate results against limits"""
try:
for category, measurements in results.items():
for param, value in measurements.items():
limit = limits.get(f"{category}.{param}")
if limit is not None and value > limit:
return False
return True
except Exception as e:
raise ValidationError(f"Results validation failed: {e}")- IEEE 802.3 224G Ethernet Specification
- High-Speed Serial Link Design Guide
- Equipment Manuals and Specifications