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By reformulating the problem into the simultaneous processing of a data and a control stream, cache miss penalties could be significantly reduced.
As we have stated in Section 1, private L2 cache organizations suffer from lower L1 cache miss latencies than shared L2 cache architectures at the expense of poor cache storage utilization.
Due to cache miss, the UIR strategy broadcasts the requested data items only after the next IR, whereas our strategy also broadcasts the requested data items after every UIR (as part of RR).
To hide instruction cache miss latency more effectively in modern microprocessors, we propose and evaluate a new fully automatic instruction prefetching scheme whereby the compiler and the hardware cooperate to launch prefetches earlier (therefore hiding more latency) while at the same time maintaining high coverage and actually reducing the impact of useless prefetches relative to today's schemes.
If, however, a prefetched block displaces a cache block which is referenced after the prefetched block has been used, this is an ordinary replacement miss since the resulting cache miss would have occurred with or without prefetching.
shows that our approach is better at reducing the L1 cache miss rate than Hashemi et al.
In MLP aware replacement policy, the algorithm computes the MLP-based costing for each cache miss and uses the MLP cost and recency to determine the cache block to be replaced.
Suppose that during the processing of supernode j, the algorithm references a datum that is already in the cache, so no cache miss occurs.
This paper presents a survey of some of the proposals that have recently appeared focusing on two of these factors: the increased cost in terms of hardware overhead that the use of directories entails, and the long cache miss latencies observed in these designs as a consequence of the indirection introduced by the access to the directory.
Adding more memory to the server does reduce the cache miss rate, but adding enough memory to achieve a significant effect is prohibitively expensive.
But the net effect on performance will depend both on improvements due to better branch prediction and on penalties due to worse cache miss rates.
Some problems with embedding DRAM on logic include bandwidth constraints and providing access to embedded DRAM after a cache miss.