Software Self-Test As A Safety Mechanism For Processing Units


The growing dependency of modern automobiles on electronic functions increases the need for a variety of integrated circuits (ICs) for safety-critical applications. Requirements coming from different in-car subsystems drives the need for chip manufacturers to create a wide range of specialized solutions. This, in turn, raises the bar for automotive IP suppliers and pushes them to offer configur... » read more

Solving The Quantum Threat With Post-Quantum Cryptography On eFPGAs


The quantum threat and post-quantum cryptography Advances in quantum computing technology threaten the security of current cryptosystems. Asymmetric cryptography algorithms that are used by modern security protocols for key exchange and digital signatures rely on the complexity of certain mathematical problems. Currently, the main problems used for asymmetric cryptography are integer f... » read more

Going Beyond The Requirements Of A Root Of Trust For Measurement With The Silicon-Proven RT-660 Root of Trust


The continuously evolving technology landscape and security requirements for systems present many challenges for device and silicon manufacturers. Nowhere is this truer than in data centers. Rambus has long recognized the need for security designs in data centers, and the Caliptra initiative discussed in this whitepaper is a welcome step towards a widespread adoption of Root of Trust designs i... » read more

How To Make The Charging Infrastructure For Electric Vehicles Smart


Renewable energies and the increasing emergence of electric vehicles are putting a strain on the electricity grid. The former are not constantly available, and the latter require additional energy while charging. This leads to the need for introducing a new, smart charging infrastructure to avoid instabilities at the grid level. This white paper explains what is involved in making a charging in... » read more

Radiation Tolerance Is Not Just For Rocket Scientists


As technology scales, soft errors from particle radiation are becoming increasingly concerning for in-field reliability. These radiation effects are called Single Event Upsets (SEU) and the frequency of the failures due to SEUs is known as the Soft Error Rate (SER). Soft errors are failures due to external sources. By contrast, hard errors refer to actual process manufacturing defects or electr... » read more

An Organic Package Designer’s Guide To Transitioning To FOWLP And 2.5D Design


The IC packaging design tool set has matured to the point where it can address not only classic plastic, organic and ceramic packaging substrates but can also address silicon substrates driven by interposer and chiplet designs. In most cases system and packaging teams do not have to abandon their existing tool set to support these designs. In fact, the packaging design tool set can offer additi... » read more

6 Oscilloscope Tricks To Get The Most Out Of Your Scope


Get the most out of your oscilloscope with these six tips covering basic triggering, probing, scaling signals, using the right acquisition mode, and more. Click here to read more. » read more

Tempus Timing Signoff Solution


The Cadence Tempus Timing Signoff Solution is the fastest static timing analysis (STA) tool in the industry today with unique distributed processing and cloud capabilities enabling hundreds of CPUs to quickly complete even the largest designs. With full foundry certification and a comprehensive set of advanced capabilities, the Tempus solution delivers SPICE-accurate results to hundreds... » read more

Overview Of TVOC And Indoor Air Quality


The aim of this white paper is to cover the basics of total volatile organic compounds (TVOC) and indoor air quality (IAQ). Volatile organic compounds are the main source for poor indoor air quality, which can affect a person’s daily life. Recommendations from various institutions and agencies regarding TVOC levels that are deemed hazardous to human health are given in the “Hazardous Condit... » read more

Multiexpert Adversarial Regularization For Robust And Data-Efficient Deep Supervised Learning


Deep neural networks (DNNs) can achieve high accuracy when there is abundant training data that has the same distribution as the test data. In practical applications, data deficiency is often a concern. For classification tasks, the lack of enough labeled images in the training set often results in overfitting. Another issue is the mismatch between the training and the test domains, which resul... » read more

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