Reliable and Energy-efficient Diabetic Retinopathy Screening using Memristor-based Neural Networks

Diabetic retinopathy (DR) is a leading cause of permanent vision loss worldwide. It refers to irreversible retinal damage caused due to elevated glucose levels and blood pressure. Regular screening for DR can facilitate its early detection and timely treatment. Neural network-based DR classifiers can be leveraged to achieve such screening in...

On the Reliability of RRAM-Based Neural Networks

Emerging device technologies such as Resistive RAMs (RRAMs) are under investigation by many researchers and semiconductor companies; not only to realize e.g., embedded non-volatile memories, but also to enable energy-efficient computing making use of new data processing paradigms such as computation-in-memory. However, such devices suffer from...

Testing RRAM and Computation-in-Memory Devices: Defects, Fault Models, and Test Solutions

Resistive random access memory (RRAM) is a promising emerging memory technology that offers dense, non-volatile memories that do not consume any static power. Furthermore, RRAMdevices can be written and read out in nanoseconds, and it is possible to use them to performcomputation-in-memory (CIM). These benefits make this technology a potential...

PVT Analysis for RRAM and STT-MRAM-based Logic Computation-in-Memory

Emerging non-volatile resistive memories like Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) and Resistive RAM (RRAM) are in the focus of today’s research. They offer promising alternative computing architectures such as computation-in-memory (CiM) to reduce the transfer overhead between CPU and memory, usually referred to as the...