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EDEN: Enabling energy-efficient, high-performance deep neural network inference using approximate DRAM
The effectiveness of deep neural networks (DNN) in vision, speech, and language
processing has prompted a tremendous demand for energy-efficient high-performance DNN …
processing has prompted a tremendous demand for energy-efficient high-performance DNN …
Circuit-level techniques for logic and memory blocks in approximate computing systemsx
This article presents an overview of circuit-level techniques used for approximate computing
(AC), including both computation and data storage units. After providing some background …
(AC), including both computation and data storage units. After providing some background …
Rebirth-FTL: Lifetime optimization via approximate storage for NAND flash memory
The lifetime of NAND flash cells significantly degrades with feature-size reductions and
multilevel cell technology. On the other hand, we have more and more approximate data …
multilevel cell technology. On the other hand, we have more and more approximate data …
Using run-time reverse-engineering to optimize DRAM refresh
The overhead of DRAM refresh is increasing with each density generation. To help offset
some of this overhead, JEDEC designed the modern Auto-Refresh command with a highly …
some of this overhead, JEDEC designed the modern Auto-Refresh command with a highly …