A primer on hardware prefetching
著者
書誌事項
A primer on hardware prefetching
（Synthesis lectures on computer architecture, 28）
Morgan & Claypool, c2014
大学図書館所蔵 件 / 全1件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references (p. 41-[52])
内容説明・目次
内容説明
Since the 1970's, microprocessor-based digital platforms have been riding Moore's law, allowing for doubling of density for the same area roughly every two years. However, whereas microprocessor fabrication has focused on increasing instruction execution rate, memory fabrication technologies have focused primarily on an increase in capacity with negligible increase in speed. This divergent trend in performance between the processors and memory has led to a phenomenon referred to as the "Memory Wall."
To overcome the memory wall, designers have resorted to a hierarchy of cache memory levels, which rely on the principal of memory access locality to reduce the observed memory access time and the performance gap between processors and memory. Unfortunately, important workload classes exhibit adverse memory access patterns that baffle the simple policies built into modern cache hierarchies to move instructions and data across cache levels. As such, processors often spend much time idling upon a demand fetch of memory blocks that miss in higher cache levels. Prefetching-predicting future memory accesses and issuing requests for the corresponding memory blocks in advance of explicit accesses-is an effective approach to hide memory access latency. There have been a myriad of proposed prefetching techniques, and nearly every modern processor includes some hardware prefetching mechanisms targeting simple and regular memory access patterns. This primer offers an overview of the various classes of hardware prefetchers for instructions and data proposed in the research literature, and presents examples of techniques incorporated into modern microprocessors.
目次
Preface
Introduction
Instruction Prefetching
Data Prefetching
Concluding Remarks
Bibliography
Author Biographies
「Nielsen BookData」 より