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The Verification Mindset


The practice of semiconductor verification has changed substantially over the years, and will continue to do so. The skillset needed for functional verification 20 years ago is hardly recognizable as a verification skillset today, and the same should be expected moving forward as design and verification becomes more abstract, the boundary of what is implemented in hardware versus firmware and s... » read more

Speeding Up AI With Vector Instructions


A search is underway across the industry to find the best way to speed up machine learning applications, and optimizing hardware for vector instructions is gaining traction as a key element in that effort. Vector instructions are a class of instructions that enable parallel processing of data sets. An entire array of integers or floating point numbers is processed in a single operation, elim... » read more

Week In Review: Auto, Security, Pervasive Computing


AI, machine learning Cadence says it has optimized its Tensilica HiFi digital signal processor IP to efficiently execute TensorFlow Lite for Microcontrollers, which are used in Google’s machine learning platform for edge. This means developers of AI/ML on the edge systems can now put better audio processing on edge devices with ML applications like keyword detection, audio scene detection, n... » read more

Week In Review: IoT, Security, Autos


Internet of Things Sensors that see in the dark, look deep into our faces and hear the impossible, were all part of ams’ CES lineup this week. ams announced that it has designed an advanced spectral ambient light sensor (ALS) for high-end mobile phone cameras. The ALS, called the AS7350, identifies the light source and makes an accurate white balance under low-light and other non-ideal condi... » read more

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

Synthesizing Hardware From Software


The ability to automatically generate optimized hardware from software was one of the primary tenets of system-level design automation that was never fully achieved. The question now is whether that will ever happen, and whether it is just a matter of having the right technology or motivation to make it possible. While high-level synthesis (HLS) did come out of this work and has proven to be... » read more

Open Source Processors: Fact Or Fiction?


Open source processors are rapidly gaining mindshare, fueled in part by early successes of RISC-V, but that interest frequently is accompanied by misinformation based on wishful thinking and a lack of understanding about what exactly open source entails. Nearly every recent conference has some mention of RISC-V in particular, and open source processors in general, whether that includes keyno... » read more

SLAM And DSP Implementation


With the introduction of simultaneous localization and mapping technology, or SLAM, there comes a need for more sophisticated DSPs to handle the required computations. To address this need, Cadence has introduced the Tensilica Vision Q7 DSP to handle the requirements of SLAM, including high performance, low power, and with an ease of development that engineers can leverage to design new and exc... » 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

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