FIGARO: Improving System Performance via Fine-Grained In-DRAM Data Relocation and Caching
Yaohua Wang, Lois Orosa, Xiangjun Peng, Yang Guo, Saugata Ghose, Minesh Patel, Jeremie S. Kim, Juan Gómez-Luna, Mohammad Sadrosadati, Nika Mansouri-Ghiasi, Onur Mutlu
摘要
Main memory, composed of DRAM, is a performance bottleneck for many applications, due to the high DRAM access latency. In-DRAM caches work to mitigate this latency by augmenting regular-latency DRAM with small-but-fast regions of DRAM that serve as a cache for the data held in the regularlatency (i.e., slow) region of DRAM. While an effective in-DRAM cache can allow a large fraction of memory requests to be served from a fast DRAM region, the latency savings are often hindered by inefficient mechanisms for migrating (i.e., relocating) copies of data into and out of the fast regions. Existing in-DRAM caches have two sources of inefficiency: (1) their data relocation granularity is an entire multi-kilobyte row of DRAM, even though much of the row may never be accessed due to poor data locality; and (2) because the relocation latency increases with the physical distance between the slow and fast regions, multiple fast regions are physically interleaved among slow regions to reduce the relocation latency, resulting in increased hardware area and manufacturing complexity.
We propose a new substrate, FIGARO, that uses existing shared global buffers among subarrays within a DRAM bank to provide support for in-DRAM data relocation across subarrays at the granularity of a single cache block. FIGARO has a distance-independent latency within a DRAM bank, and avoids complex modifications to DRAM (such as the interleaving of fast and slow regions). Using FIGARO, we design a fine-grained in-DRAM cache called FIGCache. The key idea of FIGCache is to cache only small, frequently-accessed portions of different DRAM rows in a designated region of DRAM. By caching only the parts of each row that are expected to be accessed in the near future, we can pack more of the frequently-accessed data into FIGCache, and can benefit from additional row hits in DRAM (i.e., accesses to an already-open row, which have a lower latency than accesses to an unopened row). FIGCache provides benefits for systems with both heterogeneous DRAM banks (i.e., banks with fast regions and slow regions) and conventional homogeneous DRAM banks (i.e., banks with only slow regions).
Our evaluations across a wide variety of applications show that FIGCache improves the average performance of a system using DDR4 DRAM by 16.3% and reduces average DRAM energy consumption by 7.8% for 8-core workloads, over a conventional system without in-DRAM caching. We show that FIGCache outperforms state-of-the-art in-DRAM caching techniques, and that its performance gains are robust across many system and mechanism parameters.
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引用它的顶会 Paper21
- SIMDRAM: a framework for bit-serial SIMD processing using DRAMNastaran Hajinazar, Geraldo F. Oliveira, Sven Gregorio, João Dinis Ferreira 等ASPLOS 2021 · 被引用 182 次
- BlockHammer: Preventing RowHammer at Low Cost by Blacklisting Rapidly-Accessed DRAM RowsAbdullah Giray Yaglikçi, Minesh Patel, Jeremie S. Kim, Roknoddin Azizi 等HPCA 2021 · 被引用 124 次
- Uncovering In-DRAM RowHammer Protection Mechanisms: A New Methodology, Custom RowHammer Patterns, and ImplicationsHasan Hassan, Yahya Can Tugrul, Jeremie S. Kim, Victor van der Veen 等MICRO 2021 · 被引用 79 次
- A Deeper Look into RowHammer's Sensitivities: Experimental Analysis of Real DRAM Chipsand Implications on Future Attacks and DefensesLois Orosa, Abdullah Giray Yaglikçi, Haocong Luo, Ataberk Olgun 等MICRO 2021 · 被引用 74 次
- QUAC-TRNG: High-Throughput True Random Number Generation Using Quadruple Row Activation in Commodity DRAM ChipsAtaberk Olgun, Minesh Patel, Abdullah Giray Yaglikçi, Haocong Luo 等ISCA 2021 · 被引用 49 次
它引用的顶会 Paper7
- DRAMA: Exploiting DRAM Addressing for Cross-CPU AttacksPeter Pessl, Daniel Gruss, Clémentine Maurice, Michael Schwarz 等USENIX Security 2016 · 被引用 500 次
- TRRespass: Exploiting the Many Sides of Target Row RefreshPietro Frigo, Emanuele Vannacci, Hasan Hassan, Victor van der Veen 等S&P 2020 · 被引用 274 次
- Revisiting RowHammer: An Experimental Analysis of Modern DRAM Devices and Mitigation TechniquesJeremie S. Kim, Minesh Patel, Abdullah Giray Yaglikçi, Hasan Hassan 等ISCA 2020 · 被引用 161 次
- Are We Susceptible to Rowhammer? An End-to-End Methodology for Cloud ProvidersLucian Cojocar, Jeremie S. Kim, Minesh Patel, Lillian Tsai 等S&P 2020 · 被引用 115 次
- CLR-DRAM: A Low-Cost DRAM Architecture Enabling Dynamic Capacity-Latency Trade-OffHaocong Luo, Taha Shahroodi, Hasan Hassan, Minesh Patel 等ISCA 2020 · 被引用 64 次
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