Abstract:
Compute-in-memory (CIM) is a promising approach for efficiently performing data-centric computing (such as neural network computations). Among the multiple semiconductor ...Show MoreMetadata
Abstract:
Compute-in-memory (CIM) is a promising approach for efficiently performing data-centric computing (such as neural network computations). Among the multiple semiconductor memory technologies, embedded DRAM (eDRAM), which integrates the DRAM bit cell with high-performance logic transistors, can enable efficient CIM designs. However, the silicon-based eDRAM technology suffers from poor retention time-incurring significant refresh power overhead. However, eDRAM using back-end-of-line (BEOL) integrated C -axis aligned crystalline (CAAC) indium–gallium–zinc–oxide (IGZO) transistors, exhibiting extreme low leakage, is a promising memory technology with lower refresh power overhead. A long retention time in IGZO eDRAM can enable multilevel cell functionality, which can improve its efficacy in CIM applications. In this article, we explore a capacitorless IGZO eDRAM-based multilevel cell, capable of storing 1.5 bits/cell for CIM designs focused on deep neural network (DNN) inference applications. We perform a detailed design space exploration of IGZO eDRAM sensitivity to process temperature variations for read, write, and retention operations followed by architecture-level simulations comparing performance and energy for different workloads. The effectiveness of IGZO eDRAM-based CIM architecture is evaluated using a representative neural network, and the proposed approach achieves 82% Top-1 inference accuracy for the CIFAR-10 dataset, compared with 87% software accuracy with high bit cell storage density.
Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits ( Volume: 8, Issue: 1, June 2022)
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- IEEE Keywords
- Index Terms
- Chromatography ,
- Neural Network ,
- Deep Neural Network ,
- Density Data ,
- Zinc Oxide ,
- Promising Technology ,
- Low Leakage ,
- Most Significant Bit ,
- Read Operation ,
- Memory Technologies ,
- Design Space Exploration ,
- Monte Carlo Simulation ,
- Presence Of Variants ,
- Storage Capacity ,
- End Reads ,
- Dot Product ,
- Threshold Voltage ,
- Load Data ,
- Voltage Difference ,
- Negative Voltage ,
- Resistive Random Access Memory ,
- Ferroelectric Field-effect Transistor ,
- Cache Misses ,
- Different Levels Of Values ,
- Word Line ,
- Turnitin ,
- Capacitive Coupling ,
- Random Access Memory ,
- Spin Transfer Torque ,
- Circuit Simulation
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Chromatography ,
- Neural Network ,
- Deep Neural Network ,
- Density Data ,
- Zinc Oxide ,
- Promising Technology ,
- Low Leakage ,
- Most Significant Bit ,
- Read Operation ,
- Memory Technologies ,
- Design Space Exploration ,
- Monte Carlo Simulation ,
- Presence Of Variants ,
- Storage Capacity ,
- End Reads ,
- Dot Product ,
- Threshold Voltage ,
- Load Data ,
- Voltage Difference ,
- Negative Voltage ,
- Resistive Random Access Memory ,
- Ferroelectric Field-effect Transistor ,
- Cache Misses ,
- Different Levels Of Values ,
- Word Line ,
- Turnitin ,
- Capacitive Coupling ,
- Random Access Memory ,
- Spin Transfer Torque ,
- Circuit Simulation
- Author Keywords