Week In Review: Design, Low Power


Tools & IP OneSpin Solutions debuted the Hardware Metric Calculation (HMC) App, which uses automatically extracted design information to calculate key hardware metrics to comply with functional safety standards. In particular, it focuses on automotive and autonomous driving SoCs needing to meet the highest functional safety requirements defined by the ISO 26262 standard. The HMC App calcul... » read more

Efficient Low-Cost Implementation of NB-IoT for Smart Applications


NB-IoT is an emerging technology for narrowband wireless communication standardized by 3GPP. It has been designed with a focus on minimizing end-user equipment processing requirements and power consumption to enable the massive deployment of low-cost devices for a broad range of smart applications. This white paper highlights the key challenges of NB-IoT modem design. It proposes a hardware/sof... » read more

Achieving Flexible Processing Requirements For IoT End-Node Devices


The term Internet of Things (IoT), which used to be used broadly to describe almost all connected devices, can now be seen to fall into two segments: Critical IoT and Massive IoT. Critical IoT refers to mission-critical applications such as automotive communication, industrial machines, and medical procedures where low latency is crucial, while Massive IoT is related to the billions of connecte... » read more

Using Memory Differently


Chip architects are beginning to rewrite the rules on how to choose, configure and use different types of memory, particularly for chips with AI and some advanced SoCs. Chipmakers now have a number of options and tradeoffs to consider when choosing memories, based on factors such as the application and the characteristics of the memory workload, because different memory types work better tha... » read more

Get Smart with NB-IoT


NB-IoT is an emerging technology for narrowband wireless communication standardized by 3GPP. It has been designed with a focus on minimizing end-user equipment processing requirements and power consumption to enable the massive deployment of low-cost devices for a broad range of smart applications. This white paper highlights the key challenges of NB-IoT modem design. It proposes a hardware/so... » read more

Enabling Embedded Vision Neural Network DSPs


Neural networks are now being developed in a variety of technology segments in the embedded market, from mobile to surveillance to the automotive segment. The computational and power requirements to process this data is increasing, with new methods to approach deep learning challenges emerging every day. Vision processing systems must be designed holistically, for all platforms, with hardwa... » read more

The Cost Of Accuracy


How accurate does a system need to be, and what are you willing to pay for that accuracy? There are many sources of inaccuracy throughout the development flow of electronic systems, most of which involve complex tradeoffs. Inaccuracy leaves an impact on your design in ways you are not even aware of, hidden by best practices or guard-banding. EDA tools also inject some inaccuracy. As the i... » read more

Reducing Latency, Power, and Gate Count with Floating-Point FMA


Today’s digital signal processing applications such as radar, echo cancellation, and image processing are demanding more dynamic range and computation accuracy. Floating-point arithmetic units offer better precision, higher dynamic range, and shorter development cycles when compared with fixed-point arithmetic units. Minimizing the design’s time to market is more important than ever. Algori... » read more

Formal Datapath Verification


J.T. Longino, formal verification application engineer at Synopsys, drills down into how to achieve confidence in datapath designs by applying formal solvers and methods to data transformation areas of a design rather than the control path areas. https://youtu.be/n1zO3GxEZVI     See other tech talk videos here. » read more

What Makes A Good AI Accelerator


The rapid growth and dynamic nature of AI and machine learning algorithms is sparking a rush to develop accelerators that can be optimized for different types of data. Where one general-purpose processor was considered sufficient in the past, there are now dozens vying for a slice of the market. As with any optimized system, architecting an accelerator — which is now the main processing en... » read more

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