Python-asyncio-同时向4个文件写入数据-用时比顺序写入还多呢？

问题遇到的现象和发生背景

   使用Python的asyncio，不太熟练，按照目前的理解，如果向 01.txt, 02.txt, 03.txt, 04.txt分别写入1百万条数据，如果按顺序执行，每个文件写入完成用时2秒，那总共要8秒。。。。如果用asyncio，是不是就会少很多？用时一定会少于8秒吧。。。
   我写了一段程序，实际运行后，和按顺序写的用时基本一样。。。。请高手帮忙答疑，谢谢！

问题相关代码，请勿粘贴截图

import asyncio
import time, string

now = lambda: time.time()
async def do_some_work(x):
    print('Waiting: ', x)
    await asyncio.sleep(x)
    return 'Done after {}s'.format(x)

async def do_write_file(filename):
    print('Waiting: ', filename)
    fp = open(filename, "w")
    str = string.ascii_letters
    starttime = time.time()
    for inum in range(0, 1000000):
        straa = "%05d" % inum
        fp.write(straa + " " + str + "\n")
    fp.close()
    endtime = time.time()
    print(endtime-starttime)
    return filename

start = now()
coroutine1 = do_write_file("01.txt")
coroutine2 = do_write_file("02.txt")
coroutine3 = do_write_file("03.txt")
coroutine4 = do_write_file("04.txt")
tasks = [
    asyncio.ensure_future(coroutine1),
    asyncio.ensure_future(coroutine3),
    asyncio.ensure_future(coroutine2),
    asyncio.ensure_future(coroutine4)
]
loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait(tasks))
for task in tasks:
    print('Task ret: ', task.result())
print('TIME: ', now() - start)

###### 运行结果及报错内容 
Waiting:  01.txt
1.6256601810455322
Waiting:  03.txt
1.594179391860962
Waiting:  02.txt
1.5777881145477295
Waiting:  04.txt
1.6811869144439697
Task ret:  01.txt
Task ret:  03.txt
Task ret:  02.txt
Task ret:  04.txt
TIME:  6.540212154388428

异步，需要考虑的问题核心在于机器，你的机器配置如何，比如核心多少，内存多少，磁盘IO速率如何。
这些都是影响的关键。

Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz 2.30 GHz / 24核 / 32G内存
操作系统是Win10
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