Energy versus Data Integrity Trade-Offs in Embedded High-Density Logic Compatible Dynamic Memories
Adam Teman1,a, Georgios Karakonstantis1,b, Robert Giterman2, Pascal Meinerzhagen3 and Andreas Burg1,c
1Telecommunications Circuits Lab (TCL), École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
2Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel
3Circuit Research, Intel Labs, JF3-334, 2111 NE 25th Ave, Hillsboro, OR, USA
Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2 kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.
Keywords: Embedded memories, DRAM, Refresh power, Data integrity, Energy efficiency, Error resilience.
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