Fixed and Floating FMCW Radar Signal Processing with Tensilica DSPs


Automotive advanced driver assistance system (ADAS) applications increasingly demand radar modules with better capability and performance. These applications require sophisticated radar processing algorithms and powerful digital signal processors (DSPs) to run them. Because these embedded systems have limited power and cost budgets, the DSP’s instruction set architecture (ISA) needs to be eff... » read more

Simultaneous Localization And Mapping


Amol Borkar, senior product manager at Cadence, explains how to track the movement of an object in a scene and how to match features from one image to the next using SLAM. The technology is used in everything from mobile phones to automotive and drones. » read more

ML, Edge Drive IP To Outperform Broader Chip Market


The market for third-party semiconductor IP is surging, spurred by the need for more specific capabilities across a wide variety of markets. While the IP industry is not immune to steep market declines in semiconductor industry, it does have more built-in resilience than other parts of the industry. Case in point: The top 15 semiconductor suppliers were hit with an 18% decline in 2019 first-... » 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

Looking Beyond The CPU


CPUs no longer deliver the same kind of of performance improvements as in the past, raising questions across the industry about what comes next. The growth in processing power delivered by a single CPU core began stalling out at the beginning of the decade, when power-related issues such as heat and noise forced processor companies to add more cores rather than pushing up the clock frequency... » read more

AI Begins To Reshape Chip Design


Artificial intelligence is beginning to impact semiconductor design as architects begin leveraging its capabilities to improve performance and reduce power, setting the stage for a number of foundational shifts in how chips are developed, manufactured and updated in the future. AI—and machine learning and deep learning subsets—can be used to greatly improve the functional control and pow... » read more

Where ML Works Best


Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to discuss machine learning inside and outside of EDA tools and how that will affect the future of chip and system design. What follows are excerpts of that discussion. SE: How do you see the market and use of machine learning shaping up? Devgan: There are three main areas—machine learning inside, machine lear... » read more

Tiling Is Critical For eFPGA Users: ArrayLinx Delivers


FPGA chips come in multiple sizes — modular blocks of programmable logic, DSP MACs and RAM are intermixed in different sizes and ratios then stitched together with top-level interconnect, clocking, etc and surrounded by a ring of I/Os like GPIO, SerDes, USB, etc. There is extensive engineering and top-level physical design for each distinct FPGA array and chip. eFPGA is different: Custome... » read more

AI: The Next Big Thing


The next big thing isn't actually a thing. It's a set of finely tuned statistical models. But developing, optimizing and utilizing those models, which collectively fit under the umbrella of artificial intelligence, will require some of the most advanced semiconductors ever developed. The demand for artificial intelligence is almost ubiquitous. As with all "next big things," it is a horizonta... » read more

Preparing For Bigger Changes Ahead


The semiconductor industry has undergone a fundamental shift over the past year, and it's one that will redefine chipmaking over the next decade or more. While the focus is still on building the fastest, lowest-power devices, whether that's by shrinking features or packaging them into blazing-fast 2.5D or fan-out configurations, these devices are being customized for specific use cases much ... » read more

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