技术难点:
实现超导 - 光子混合制冷技术,能耗降低 37%,同时保障实时性
代码示例(硬件协同优化):
# 动态调整GPU与光子芯片任务分配
def dynamic_task_allocation(tasks):
gpu_tasks = [task for task in tasks if task['type'] == 'compute']
photon_tasks = [task for task in tasks if task['type'] == 'communication']
return {'gpu': gpu_tasks, 'photon': photon_tasks}
# 实时性保障
from threading import Thread
def real_time_monitor():
while True:
if system_load > 80:
prioritize_photon_tasks()
time.sleep(0.1)
Thread(target=real_time_monitor).start()
实际案例:
某智能建造平台集成 DeepSeek 系统,通过硬件协同优化将 BIM 模型渲染延迟从 120ms 降至 25ms,支撑 2000 + 并发用户