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Reinforcement bipolar read: addressing read disturb in RRAM

Brinkhorst, Douwe (author)

Memory advances have not kept up with computing demands. Emerging device technology Resistive RAM (RRAM) addresses this by enabling computation-in-memory. However, RRAM suffers from read disturb, limiting viability. While earlier work has had some success in reducing read disturb by switching the read current direction (a bipolar read scheme),...

master thesis 2024

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

Diware, S.S. (author), Chilakala, Koteswararao (author), Joshi, Rajiv V. (author), Hamdioui, S. (author), Bishnoi, R.K. (author)

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...

journal article 2024

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Automatic defect identification during RRAM characterization

Heidekamp, Mathijs (author)

Resistive random access memory (RRAM) is an emerging memory technology that has the potential to replace dynamic random access memory (DRAM) or FLASH. The current memory technology suffer from scalability issues. RRAM can be used as potential replacement for Flash and DRAM. RRAM stores information using resistance states instead of charge. RRAM...

master thesis 2023

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Data Background-Based Test Development for All Interconnect and Contact Defects in RRAMs

Xun, H. (author), Fieback, M. (author), Yuan, S. (author), Zhang, Ziwei (author), Taouil, M. (author), Hamdioui, S. (author)

Resistive Random Access Memory (RRAM) is a potential technology to replace conventional memories by providing low power consumption and high-density storage. As various manufacturing vendors make significant efforts to push it to high-volume production and commercialization, high-quality and efficient test solutions are of great importance. This...

conference paper 2023

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Online Fault Detection and Diagnosis in RRAM

Fieback, M. (author), Bradarić, Filip (author), Taouil, M. (author), Hamdioui, S. (author)

Resistive Random Access Memory (RRAM, or ReRAM) is a promising memory technology to replace Flash because of its low power consumption, high storage density, and simple integration in existing IC production processes. This has motivated many companies to invest in this technology. However, RRAM manufacturing introduces new failure mechanisms and...

conference paper 2023

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Stopping Voltage-Dependent PCM and RRAM-Based Neuromorphic Characteristics of Germanium Telluride

Abbas, Yawar (author), Ansari, Sumayya M. (author), Taha, Inas (author), Abunahla, H.N. (author), Khan, Muhammad Umair (author), Rezeq, Moh'd (author), Aldosari, Haila M. (author), Mohammad, Baker (author)

Recently, phase change chalcogenides, such as monochalcogenides, are reported as switching materials for conduction-bridge-based memristors. However, the switching mechanism focused on the formation and rupture of an Ag filament during the SET and RESET, neglecting the contributions of the phase change phenomenon and the distribution and re...

journal article 2023

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Device-Aware Test for Ion Depletion Defects in RRAMs

Xun, H. (author), Yuan, S. (author), Fieback, M. (author), Taouil, M. (author), Hamdioui, S. (author), Aziza, Hassen (author)

Many companies are heavily investing in the commercialization of Resistive Random Access Memories (RRAMs). This calls for a comprehensive understanding of manufacturing defects to develop efficient and high-quality test and diagnosis solutions to push high-volume production. This paper identifies and characterizes a new defect based on silicon...

conference paper 2023

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Severity-based Hierarchical ECG Classification using Neural Networks

Diware, S.S. (author), Dash, Sudeshna (author), Gebregiorgis, A.B. (author), Joshi, Rajiv V. (author), Strydis, C. (author), Hamdioui, S. (author), Bishnoi, R.K. (author)

Timely detection of cardiac arrhythmia characterized by abnormal heartbeats can help in the early diagnosis and treatment of cardiovascular diseases. Wearable healthcare devices typically use neural networks to provide the most convenient way of continuously monitoring heart activity for arrhythmia detection. However, it is challenging to...

journal article 2023

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On the Reliability of RRAM-Based Neural Networks

Aziza, Hassen (author), Zambelli, Cristian (author), Hamdioui, S. (author), Diware, S.S. (author), Bishnoi, R.K. (author), Gebregiorgis, A.B. (author)

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...

conference paper 2023

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Characterization and Test of Intermittent Over RESET in RRAMs

Xun, H. (author), Fieback, M. (author), Yuan, S. (author), Aziza, Hassen (author), Heidekamp, Mathijs (author), Copetti, Thiago (author), Poehls, Leticia Bolzani (author), Taouil, M. (author), Hamdioui, S. (author)

Resistive Random Access Memories (RRAMs) are being commercialized with significant investment from several semiconductor companies. In order to provide efficient and high-quality test solutions to push high-volume production, a comprehensive understanding of manufacturing defects is significantly required. This paper identifies and characterizes...

conference paper 2023

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

Fieback, M. (author)

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...

doctoral thesis 2022

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Detecting Unique RRAM Faults: High Fault Coverage Design-For-Testability Scheme

Bradarić, Filip (author)

Resistive Random-Access Memory (RRAM) is an emerging memory technology that has the possibility to compete with mainstream memory technologies such as Dynamic Random-Access Memory (DRAM) and flash memory. The reason why RRAM has not seen mass adoption yet is due to its defect-prone nature. The resistance of RRAM can assume any value within its...

master thesis 2022

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Defects, Fault Modeling, and Test Development Framework for RRAMs

Fieback, M. (author), Cardoso Medeiros, G. (author), Wu, L. (author), Aziza, Hassen (author), Bishnoi, R.K. (author), Taouil, M. (author), Hamdioui, S. (author)

Resistive RAM (RRAM) is a promising technology to replace traditional technologies such as Flash, because of its low energy consumption, CMOS compatibility, and high density. Many companies are prototyping this technology to validate its potential. Bringing this technology to the market requires high-quality tests to ensure customer...

journal article 2022

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Structured Test Development Approach for Computation-in-Memory Architectures

Fieback, M. (author), Taouil, M. (author), Hamdioui, S. (author)

Testing of Computation-in-Memory (CIM) designs based on emerging non-volatile memory technologies, such as resistive RAM (RRAM), is fundamentally different from testing traditional memories. Such designs allow not only for data storage (i.e., memory configuration) but also for the execution of logical and arithmetic operations (i.e., computing...

conference paper 2022

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Exploring an On-Chip Sensor to Detect Unique Faults in RRAMs

Copetti, T.S. (author), Nilovic, M. (author), Fieback, M. (author), Gemmeke, T. (author), Hamdioui, S. (author), Bolzani Poehls, L.M. (author)

Memristive devices have become promising candidates to complement and/or replace the CMOS technology, due to their CMOS manufacturing process compatibility, zero standby power consumption, high scalability, as well as their capability to implement high-density memories and new computing paradigms. Despite these advantages, memristive devices are...

conference paper 2022

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

Singh, A. (author), Fieback, M. (author), Bishnoi, R.K. (author), Bradarić, Filip (author), Gebregiorgis, A.B. (author), Joshi, R.V. (author), Hamdioui, S. (author)

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...

conference paper 2022

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RRAM Crossbar-Based Fault-Tolerant Binary Neural Networks (BNNs)

Gebregiorgis, A.B. (author), Zografou, Artemis (author), Hamdioui, S. (author)

Computation-In Memory (CIM) using RRAM crossbar array is a promising solution to realize energy-efficient neuromorphic hardware, such as Binary Neural Networks (BNNs). However, RRAM faults restrict the applicability of CIM for BNN implementation. To address this issue, we propose a fault tolerance framework to mitigate the impact of RRAM faults...

conference paper 2022

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Energy-Efficient SNN Implementation Using RRAM-Based Computation In-Memory (CIM)

El Arrassi, A.E. (author), Gebregiorgis, A.B. (author), Haddadi, Anass El (author), Hamdioui, S. (author)

Spiking Neural Networks (SNNs) can drastically improve the energy efficiency of neuromorphic computing through network sparsity and event-driven execution. Thus, SNNs have the potential to support practical cognitive tasks on resource constrained platforms, such as edge devices. To realize this, SNN requires energy-efficient hardware which can...

conference paper 2022

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

Fieback, M. (author), Münch, Christopher (author), Gebregiorgis, A.B. (author), Cardoso Medeiros, G. (author), Taouil, M. (author), Hamdioui, S. (author), Tahoori, Mehdi (author)

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...

conference paper 2022

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RRAM-based Low-Power Neuromorphic Computing Engine for Space Applications

Rudge, Zacharia (author)

With recent breakthroughs in AI and deep learning, applying these techniques to on-board computers for space applications has grown in interest to engineers on space applications. The space field brings its own challenges, such as reliability and power restrictions. The proposed solution in this work concerns a neuromorphic accelerator for a...

master thesis 2021