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| """
IMS 芯片选型决策框架
考虑: 算力/功耗/生态/成本/风险
"""
CHIP_MATRIX = {
'Qualcomm QCS8255': {
'ai_tops': 26,
'power_w': 5,
'ecosystem': '成熟（SNPE/QNN）',
'dms_support': '✅ 验证',
'oms_support': '✅ 基础',
'cost': '中',
'risk': '低',
'recommend': '当前首选'
},
'NXP S32G + Ambarella': {
'ai_tops': '15+ (CVflow)',
'power_w': 8,
'ecosystem': '待整合',
'dms_support': '⚠️ 需适配',
'oms_support': '✅ 视觉强',
'cost': '中高',
'risk': '中（收购不确定性）',
'recommend': '观察'
},
'TI TDA4VL': {
'ai_tops': 8,
'power_w': 5,
'ecosystem': 'TI DL RT',
'dms_support': '✅ 验证',
'oms_support': '⚠️ 算力有限',
'cost': '低',
'risk': '低',
'recommend': '成本优先'
}
}
def evaluate_chip(requirements: dict) -> list:
"""
Args:
requirements: {'dms': True, 'oms': True, 'cpd': False, 'budget': 'mid'}
Returns:
recommendations: sorted list
"""
scores = {}
for chip, specs in CHIP_MATRIX.items():
score = 0
if requirements.get('dms') and specs['dms_support'] == '✅ 验证':
score += 3
if requirements.get('oms') and specs['oms_support'] in ['✅ 基础', '✅ 视觉强']:
score += 2
if requirements.get('budget') == 'mid' and specs['cost'] in ['中', '中高']:
score += 1
if specs['risk'] == '低':
score += 2
scores[chip] = score
return sorted(scores.items(), key=lambda x: -x[1])
if __name__ == "__main__":
recs = evaluate_chip({'dms': True, 'oms': True, 'budget': 'mid'})
for chip, score in recs:
print(f"{chip}: {score} 分 → {CHIP_MATRIX[chip]['recommend']}")
|