Selection

April 3, 2019

Understanding DDR SDRAM memory choices

This article explains which form of DRAM memory is best for your SoC application, comparing DDR variants, types of DIMM, mobile and low-power versions, graphics memory and 3D stacks.
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March 26, 2019

High-level synthesis for AI: Part One

The computational and algorithmic demands made by computer vision systems highlight HLS' value for AI system development.
March 19, 2019

Using advanced IP to build SoCs for hyperscale data centres

SoC suppliers building the key components for hyperscale data centres need access to the latest IP to handle functions such as PCIe, DDR5, cache coherency, NVMe SSDs, and the highest-bandwidth Ethernet implementations.
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March 1, 2019

Accelerating the implementation of application-specific processors

Application-specific processors can provide high performance for specialised tasks at low energy cost.
January 25, 2019

Optimizing the hardware implementation of machine learning algorithms

Optimizing the way in which machine learning algorithms are implemented in hardware will be a major differentiator for SoCs, especially for edge devices.
December 14, 2018

The antifuse advantage for one-time programmable non-volatile memory

Antifuse-based OTP NVM is highly scalable, has the area efficiency to enable macros  of megabit capacities, and offers low read power.
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November 5, 2018
Morten Christiansen is technical marketing manager for Synopsys’ DesignWare USB and DisplayPort IP.

Understanding USB 3.2 and Type-C

The basics of USB 3.2, how to implement it in an SoC, and how USB Type-C connectors and cables are used in USB 3.2 systems.
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October 16, 2018
Dana Neustadter is a senior manager of product marketing for Synopsys’ Security IP solutions.

Why AI needs security

As AI becomes pervasive in computing applications, so too does the need for high-grade security in all levels of the system.
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October 9, 2018

Using threat models and risk assessments to define device security requirements

The proliferation of attacks against embedded systems is making designers realize that they need to do more to secure their products and ecosystems.
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September 23, 2018
Gordon Cooper

Flexible embedded vision processing architectures for machine-learning applications

Machine-learning strategies for embedded vision are evolving so quickly that designers need access to flexible, heterogenous processor architectures that can adapt as the algorithms evolve.
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