A 115.1 TOPS/W, 12.1 TOPS/mm²Computation-in-Memory using Ring-Oscillator based ADC for Edge AI

Analog computation-in-memory (CIM) architecture alleviates massive data movement between the memory and the processor, thus promising great prospects to accelerate certain computational tasks in an energy-efficient manner. However, data converters involved in these architectures typically achieve the required computing accuracy at the expense...

Accurate and Energy-Efficient Bit-Slicing for RRAM-Based Neural Networks

Computation-in-memory (CIM) paradigm leverages emerging memory technologies such as resistive random access memories (RRAMs) to process the data within the memory itself. This alleviates the memory-processor bottleneck resulting in much higher hardware efficiency compared to von-Neumann architecture-based conventional hardware. Hence, CIM...

Accelerating RRAM Testing with a Low-cost Computation-in-Memory based DFT

Emerging non-volatile resistive RAM (RRAM) device technology has shown great potential to cultivate not only high-density memory storage, but also energy-efficient computing units. However, the unique challenges related to RRAM fabrication process render the traditional memory testing solutions inefficient and inadequate for high product quality...

Referencing-in-Array Scheme for RRAM-based CIM Architecture

Resistive random access memory (RRAM) based computation-in-memory (CIM) architectures are attracting a lot of attention due to their potential in performing fast and energy-efficient computing. However, the RRAM variability and non-idealities limit the computing accuracy of such architectures, especially for multi-operand logic operations....

CIM-based Robust Logic Accelerator using 28 nm STT-MRAM Characterization Chip Tape-out

Spin-transfer torque magnetic random access memory (STT-MRAM) based computation-in-memory (CIM) architectures have shown great prospects for an energy-efficient computing. However, device variations and non-idealities narrow down the sensing margin that severely impacts the computing accuracy. In this work, we propose an adaptive referencing...