同义地址压缩以减少数据TLB中的能量

C. Ballapuram, H. Lee, Milos Prvulović
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引用次数: 8

摘要

现代处理器每个周期可以发出和执行多条指令,通常同时执行多个内存操作。为了减少由于资源冲突造成的停机,大多数处理器使用多端口L1缓存和tlb来支持并发内存访问。在本文中,作者观察到一个周期内的数据TLB查找和跨连续周期的数据TLB查找通常是同义的——它们到同一个页面。为了利用这一发现,提出了两种新的机制——地址转换请求的周期内压缩和周期间压缩,以节省数据TLB中的能量。结果表明,在传统的d-TLB中,使用周期内压缩可实现27%的平均节能,使用周期间压缩可实现42%的平均节能,而在语义感知的d-TLB中,使用周期间压缩可实现56%的平均节能。当这两种压缩技术结合在一起并应用于i-TLB和语义感知的d- tlb时,可以获得76%(最高87%)的平均节能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synonymous address compaction for energy reduction in data TLB
Modern processors can issue and execute multiple instructions per cycle, often performing multiple memory operations simultaneously. To reduce stalls due to resource conflicts, most processors employ multi-ported L1 caches and TLBs to enable concurrent memory accesses. In this paper, the authors observed that data TLB lookups within a cycle and across consecutive cycles are often synonymous - they go to the same page. To exploit this finding, two new mechanisms were proposed - intra-cycle compaction and inter-cycle compaction of address translation requests in order to save energy in the data TLB. The results showed that average energy savings of 27% using intra-cycle, 42% using inter-cycle in a conventional d-TLB, and 56% using inter-cycle compaction in semantic-aware d-TLBs can be achieved. When these 2 compaction techniques are combined together and applied to both the i-TLB and semantic-aware d-TLBs, an average energy savings of 76% (up to 87%) is obtained.
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