ABSTRACT

An increasing number of architectures provide virtual memory support through software-managed TLBs. However, software management can impose considerable penalties, which are highly dependent on the operating system's structure and its use of virtual memory. This work explores software-managed TLB design tradeoffs and their interaction with a range of operating systems including monolithic and microkernel designs. Through hardware monitoring and simulations, we explore TLB performance for benchmarks running on a MIPS R2000-based workstation running Ultrix, OSF/1, and three versions of mach 3.0. Results: New operating systems are changing the relative frequency of different types of TLB misses, some of which may not be efficiently handled by current architectures. For the same application binaries, total TLB service time varies by as much as an order of magnitude under different operating systems. Reducing the handling cost for kernel TLB misses reduces total TLB service time up to 40%. For TLBs between 32 and 128 slots, each doubling of the TLB size reduces total TLB service time up to 50%.

Previous branch prediction studies have relied primarily upon the SPECint89 and SPECint92 benchmarks for evaluation. Most of these benchrnarb exercise a very small amount of code. As a consequence, the resources required by these schemes for accurate predictions of larger programs have not been clear Moreovem any of these studies have simulated a very limited number of configurations.Here we report on simulations of a variety of branch prediction schemes using a set of relatively large benchmark programs that we believe to be more representative of likely system workloads.We have examined the sensitivity of these prediction schemes tovariation in workload, in resources, andin design and configuration.We show that for predictors with small available resources, aliasing between distinct branches can have the dominant injluence on prediction accuracy. For global history based schemes, such as GAs andgshare, aliasing in the predictor table can eliminate any advantage gained through inter branch correlation. For self-history based prediction scheme, such as PAs, it is aliasing inthebuffer recording branch history, rather than thepredictor table, that poses problems. Past studies have sometimes confused these effects and allocated resources incorrectly.

Abstract

Abstract