撰写一个cache模拟器,模拟cache不同配置下的命中率。 语言不限,C/C++/Java/Python等各种语言均可。 使用提供的trace文件进行评测。 要求能输入以下Cache配置参数对不同配置下的Cache命中率进行统计。 (1)Sizes: 1024, 2048, 4096, 8192, 16384 bytes (2)Block size: 8 bytes,16 bytes,32bytes (3)Associativities: Direct Mapped, 2-way, 4-way, 8-way (4)Replacement Policy: LRU, FIFO,Random 不用做图形化输入界面,只要能输入参数即可。 附件提供的trace.txt文件为cache访问的地址序列,每行是一个16进制的访存地址(32位的字节地址)。假设cache初始化时为空,要求模拟出访问全部地址之后总的命中率是多少。
时间: 2024-03-14 09:49:21 浏览: 78
好的,我明白了。这是一个比较复杂的问题,需要写一个cache模拟器,模拟不同配置下的命中率。下面是一个简单的Python程序,可以实现这个功能。
```python
import sys
def read_trace(filename):
trace = []
with open(filename, 'r') as f:
for line in f:
trace.append(int(line.strip(), 16))
return trace
class Cache:
def __init__(self, size, block_size, associativity, replacement_policy):
self.size = size
self.block_size = block_size
self.associativity = associativity
self.replacement_policy = replacement_policy
self.num_sets = size // (block_size * associativity)
self.sets = [[None] * associativity for i in range(self.num_sets)]
self.access_time = 0
self.hit_count = 0
self.miss_count = 0
def find_block(self, addr):
set_index = (addr // self.block_size) % self.num_sets
for i, block in enumerate(self.sets[set_index]):
if block is None:
return set_index, i
if block == addr:
return set_index, i
return set_index, -1
def access(self, addr):
set_index, block_index = self.find_block(addr)
if block_index == -1:
self.miss_count += 1
block_index = self.replacement_policy(self.sets[set_index])
self.sets[set_index][block_index] = addr
else:
self.hit_count += 1
self.access_time += 1
def print_stats(self):
print('Cache size: {} bytes'.format(self.size))
print('Block size: {} bytes'.format(self.block_size))
print('Associativity: {}'.format(self.associativity))
print('Replacement Policy: {}'.format(self.replacement_policy.__name__))
print('Access time: {}'.format(self.access_time))
print('Hit count: {}'.format(self.hit_count))
print('Miss count: {}'.format(self.miss_count))
print('Hit rate: {:.2f}%'.format(100 * self.hit_count / (self.hit_count + self.miss_count)))
def lru_replacement_policy(blocks):
lru_index = None
lru_time = sys.maxsize
for i, block in enumerate(blocks):
if block is None:
return i
if block['_time'] < lru_time:
lru_index = i
lru_time = block['_time']
return lru_index
def fifo_replacement_policy(blocks):
fifo_index = None
fifo_time = sys.maxsize
for i, block in enumerate(blocks):
if block is None:
return i
if block['_time'] < fifo_time:
fifo_index = i
fifo_time = block['_time']
return fifo_index
def random_replacement_policy(blocks):
return random.randrange(len(blocks))
def simulate_cache(size, block_size, associativity, replacement_policy, trace):
cache = Cache(size, block_size, associativity, replacement_policy)
for addr in trace:
cache.access(addr)
cache.print_stats()
if __name__ == '__main__':
trace = read_trace('trace.txt')
for size in [1024, 2048, 4096, 8192, 16384]:
for block_size in [8, 16, 32]:
for associativity in [1, 2, 4, 8]:
for replacement_policy in [lru_replacement_policy, fifo_replacement_policy, random_replacement_policy]:
print('Cache Configuration: size={}, block_size={}, associativity={}, replacement_policy={}'.format(size, block_size, associativity, replacement_policy.__name__))
simulate_cache(size, block_size, associativity, replacement_policy, trace)
```
这个程序使用了一个Cache类来模拟cache。它有一个大小、块大小、关联度和替换策略作为参数。它还有一个find_block方法,用于查找给定地址的块。它还有一个access方法,用于访问给定地址的块。最后,它有一个print_stats方法,用于打印命中率和其他统计信息。
在主程序中,我们使用read_trace函数从文件中读取跟踪数据。然后我们使用四个嵌套的循环来测试不同的cache配置。对于每个配置,我们使用simulate_cache函数来模拟cache,并打印出命中率和其他统计信息。
这个程序使用LRU、FIFO和随机替换策略来模拟cache。这些策略都是常见的替换策略,可以根据实际需要进行选择。
希望这个程序对你有所帮助!
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