From Silicon To Software

Archive for the 'Machine Learning' Category

 

PrimeSim Continuum Meets the Challenge of Hyper-Convergent ICs with Faster SPICE Engines and a More Unified Simulation Workflow

Learn how PrimeSim Continuum, our new IC design solution, delivers the IC verification tools & SPICE simulation speed needed for modern hyper-convergent ICs.

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Posted in 3D-ICs, EDA, Machine Learning, Prototyping, Verification

 

Onward and Upward: Enhancing 3DIC Design Productivity with a Unified Platform

3D ICs help SoC designers extend the design scale beyond Moore’s Law; learn how unified 3D IC design tools enable faster convergence for multi-die chips.

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Posted in 3D-ICs, 5G, Artificial Intelligence, HPC, Machine Learning

 

Why Datapath Validation Is Important—and How HECTOR Technology Can Help

With DVCon 2021 on the horizon we share a primer on our datapath verification technology HECTOR, exploring its impact on machine learning & AI chip design.

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Posted in Artificial Intelligence, Machine Learning, Verification

 

How Machine Learning Enables Faster, More Accurate 3D Medical Image Segmentation

Learn how machine learning is transforming 3D Image Segmentation for more efficient medical imaging, saving medical clinics hours and exporting high-quality 3D models from complex datasets.

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Posted in Machine Learning

 

Smart IoT Edge Applications Require Lower Power Processing

Low-power processing is essential for Smart Edge IoT applications. See what this means for smart home speakers and other devices enabled by machine learning.

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Posted in Internet of Things, Machine Learning

 

Harnessing the Power of Women in Tech: a USA Today Feature

Women play vital roles in developing the tools that engineers around the world use to design smart chips and develop secure code for the amazing devices that are changing the way we work and play. USA Today recently featured three Synopsys engineers, who reflect on their experiences as women in tech and offer advice on carving out success in a male-dominated field.

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Posted in Application Security, Artificial Intelligence, Automotive, Cryptography, EDA, Healthcare, Internet of Things, IP, Machine Learning, Malware, Optical Design, Privacy, Quantum Computing, Robotics, Security, Superconducting Electronics, TCAD

 

Machine Learning Finds New Exoplanets in Existing NASA Database

Using previously studied data from NASA’s Kepler Space Telescope, a Google machine learning algorithm discovered two new planets orbiting a nearby star already known to have six planets. At a total of eight planets, that system matches our own solar system. It also begs a question: How many other planetary systems might be hiding in previously analyzed data?

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Posted in Artificial Intelligence, Machine Learning