Level-0 (L0) caches have been proposed in the past as an inexpensive way to improve performance and reduce energy consumption in resource-constrained embedded processors. This paper proposes new L0 data cache organizations using the assumption that an L0 hit/miss determination can be completed prior to the L1 access. This is a realistic assumption for very small L0 caches that can nevertheless deliver significant miss rate and/or energy reduction. The key issue for such caches is how and when to move data between the L0 and L1 caches. The first new cache, a flow cache, targets a conflict miss reduction in a direct-mapped L1 cache. It offers a simpler hardware design and uses on average 10% less dynamic energy than the victim cache with nearly identical performance. The second new cache, a hit cache, reduces the dynamic energy consumption in a set-associative L1 cache by 30% without impacting performance. A variant of this policy reduces the dynamic energy consumption by up to 50%, with 5% performance degradation.

Cache management policies such as replacement, bypass, or shared cache partitioning have been relying on data reuse behavior to predict the future. This paper proposes a new way to use dynamic reuse distances to further improve such policies. A new replacement policy is proposed which prevents replacing a cache line until a certain number of accesses to its cache set, called a Protecting Distance (PD). The policy protects a cache line long enough for it to be reused, but not beyond that to avoid cache pollution. This can be combined with a bypass mechanism that also relies on dynamic reuse analysis to bypass lines with less expected reuse. A miss fetch is bypassed if there are no unprotected lines. A hit rate model based on dynamic reuse history is proposed and the PD that maximizes the hit rate is dynamically computed. The PD is recomputed periodically to track a program's memory access behavior and phases. Next, a new multi-core cache partitioning policy is proposed using the concept of protection. It manages lifetimes of lines from different cores (threads) in such a way that the overall hit rate is maximized. The average per-thread lifetime is reduced by decreasing the thread's PD. The single-core PD-based replacement policy with bypass achieves an average speedup of 4.2% over the DIP policy, while the average speedups over DIP are 1.5% for dynamic RRIP (DRRIP) and 1.6% for sampling dead-block prediction (SDP). The 16-core PD-based partitioning policy improves the average weighted IPC by 5.2%, throughput by 6.4% and fairness by 9.9% over thread-aware DRRIP (TA-DRRIP). The required hardware is evaluated and the overhead is shown to be manageable.