Answer :
To determine if a change to cache design results in improved performance, one must calculate the effect on average access time, considering factors like hit ratio, access time, and miss rate. The provided scenario demonstrates calculating hit and miss rates for a cache with given load and store instructions. Key factors in cache performance include the level of memory hierarchy and exploiting data localities.
To assess whether a change in the L1 cache design that increases the hit ratio from 0.95 to 0.97 but also increases access time from 1 ns to 1.5 ns results in improved performance, we must examine the effect on the system's average access time. Improved performance is achieved if the decreased miss rate, combined with the higher access time, still lowers the average memory access time. This requires calculating the average access time before and after the change and comparing the two.
For the given scenario, where a program has 2,000 load and store instructions out of which 1,250 data values are in cache, we can calculate the hit rate and miss rate for the cache as follows:
- Hit rate = Number of hits / Total number of load and store instructions = 1,250 / 2,000 = 0.625 or 62.5%
- Miss rate = 1 - Hit rate = 1 - 0.625 = 0.375 or 37.5%
Understanding the memory hierarchy, cache is essential to effectively design and improve computer systems. The cache memory, placed at the highest level of memory hierarchy, exploits temporal and spatial localities to predict and serve the processor's data requirements with lower latency compared to other memory levels like main memory.
When considering any changes to cache design, one needs to consider the interplay between hit ratio, access time, and the ensuing effects on the average access time. This requires a balance, as sometimes increasing the hit rate can result in higher access times, which could negate the benefits of a better hit ratio if the miss penalty is severe or if memory accesses dominate the program's execution time.
