Lune

HPCA2025顶会

Efficient Caching with A Tag-enhanced DRAM

Maryam Babaie, Ayaz Akram, Wendy Elsasser, Brent Haukness, Michael R. Miller, Taeksang Song, Thomas Vogelsang, Steven C. Woo, Jason Lowe-Power

2025年份
2被引次数

摘要

As SRAM-based caches are hitting a scaling wall, manufacturers are integrating DRAM-based caches into system designs to continue increasing cache sizes. While DRAM caches can improve the performance of memory systems, existing DRAM cache designs suffer from high miss penalties, wasted data movement, and interference between misses and demands. In this paper, we propose TDRAM, a novel DRAM microarchitecture tailored for caching. TDRAM enhances existing DRAM, such as HBM3, by adding small, low-latency mats to store tags and metadata on the same die as the data mats. These mats enable tag and data access in lockstep, in-DRAM tag comparison, and conditional data response based on the comparison result (reducing wasted data transfers), akin to SRAM cache mechanisms. TDRAM further optimizes hit and miss latencies through opportunistic early tag probing. Moreover, TDRAM introduces a flush buffer to store conflicting dirty data on write misses, eliminating data bus turnaround delays on write demands. We evaluate TDRAM in a full-system simulation using a set of HPC workloads with large memory footprints, showing that TDRAM, on average, provides 2.65×2.65 \times faster tag checks, 1.23×1.23 \times speedup, and 21% less energy consumption compared to state-of-the-art commercial and research designs.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

它引用的顶会 Paper6

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖