Affiliation:
1. Rice University, Houston, TX, USA
Abstract
Data-intensive computing applications are using more and more memory and are placing an increasing load on the virtual memory system. While the use of large pages can help alleviate the overhead of address translation, they limit the control the operating system has over memory allocation and protection. We present a novel device, the SpecTLB, that exploits the predictable behavior of reservation-based physical memory allocators to interpolate address translations.
Our device provides speculative translations for many TLB misses on small pages without referencing the page table. While these interpolations must be confirmed, doing so can be done in parallel with speculative execution. This effectively hides the execution latency of these TLB misses. In simulation, the SpecTLB is able to overlap an average of 57% of page table walks with successful speculative execution over a wide variety of applications. We also show that the SpecTLB outperforms a state-of-the-art TLB prefetching scheme for virtually all tested applications with significant TLB miss rates. Moreover, we show that the SpecTLB is efficient since mispredictions are extremely rare, occurring in less than 1% of TLB misses. In essense, the SpecTLB effectively enables the use of small pages to achieve fine-grained allocation and protection, while avoiding the associated latency penalties of small pages.
Publisher
Association for Computing Machinery (ACM)
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