Early detection of malign patterns in patients' biological signals can save millions of lives.
Despite the steady improvement of artificial intelligence–based techniques, the practical …

With the rise of the Internet of Things (IoT), a huge market for so-called smart edge-devices
is foreseen for millions of applications, like personalized healthcare and smart robotics …

We present a comprehensive evaluation of the robustness and explainability of ResNet-like
models in the context of Unintended Radiated Emission (URE) classification and suggest a …

Processing in-memory has the potential to break von-Neumann based design principles and
unleash exascale computing capabilities. A rudimentary problem for in-memory paradigms …

Emerging computing applications (such as big-data and Internet-of-things) are extremely
demanding in terms of storage, energy and computational efficiency, while todays …

The traditional Von-Neumann architecture is reaching its limits and finding it difficult to cope
up with the ever-increasing demands of modern workloads like artificial intelligence. This …

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 …

The next wave of scientific discovery is predicated on unleashing beyond-exascale
simulation capabilities using in-memory computing. Path-based computing is a promising in …

Flow-based computing is a digital in-memory computing paradigm with tremendous
potential. Its favorable characteristics, such as high robustness, low energy consumption …

Testing of Computation-in-Memory (CIM) designs based on emerging non-volatile memory
technologies, such as resistive RAM (RRAM), is fundamentally different from testing …