Temporal prefetching offers great potential, but this potential is difficult to achieve because of the need to store large amounts of prefetcher metadata off chip. To reduce the latency and traffic of off-chip metadata accesses, recent advances in temporal prefetching have proposed increasingly complex mechanisms that cache and prefetch this off-chip metadata. This paper suggests a return to simplicity: We present a temporal prefetcher whose metadata resides entirely on chip. The key insights are (1) only a small portion of prefetcher metadata is important, and (2) for most workloads with irregular accesses, the benefits of an effective prefetcher outweigh the marginal benefits of a larger data cache. Thus, our solution, the Triage prefetcher, identifies important metadata and uses a portion of the LLC to store this metadata, and it dynamically partitions the LLC between data and metadata.

A memory rename table for improved performance, reduced complexity, and reduced energy consumption is proposed and evaluated. It gives an average 8.7% speedup and 7.9% reduction in core and cache energy. The evaluation employs a simulation model for an out-of-order core, similar to the ARM Cortex A15, and McPAT for energy measurements. The improvements are the result of filtering nearly half (45.4%) of memory accesses before they go to cache. Complexity is reduced by replacement of a load store queue with a scalable renaming system. The changes are transparent to the ISA.

In this work we investigate the sources of error in gem5-a state-of-the-art computer simulator-by validating it against a real hardware platform: the ARM Versatile Express TC2 development board. We design a custom gem5 configuration and make several changes to the simulator itself in order to more closely match the Versatile Express TC2 board. With the modifications we make to the simulator, we are able to achieve a mean percentage runtime error of 5% and a mean absolute percentage runtime error of 13% for the SPEC CPU2006 benchmarks. For the PARSEC benchmarks we achieve a mean percentage runtime error of -11% and -12% for single and dual-core runs respectively, and a mean absolute percentage runtime error of 16% and 17% for single and dual-core runs respectively. While prior work typically considers only runtime accuracy, we extend our investigation to include several key microarchitectural statistics as well, showing that we can achieve accuracy within 20% on average for a majority of them. Much of this error is likely from modeling similar, but not identical components.

Just-in-time compilation with dynamic code optimization is often used to help improve the performance of applications that utilize high-level languages and virtual run-time environments, such as those found in smartphones. Just-in-time compilation introduces additional overhead into the instruction fetch stage of a processor that is particularly problematic for user applications-instruction cache invalidation due to the use of self-modifying code. This software-assisted cache coherence serializes cache line invalidations, or causes a costly invalidation of the entire instruction cache, and prevents useful instructions from being fetched for the period during which the stale instructions are being invalidated. This overhead is not acceptable for user applications, which are expected to respond quickly.