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Most Recent Guides & Forecasts

A Guide to Processors for Deep Learning
Covers processors for accelerating deep learning, neural networks, and vision processing for AI training and inference in data centers, autonomous vehicles, and client devices.
Communications Semiconductor Market Forecast 2019-2024
Provides five-year revenue forecasts for many categories of communications semiconductors, including Ethernet products, embedded and server processors, and FPGAs.
Communications Semiconductor Market Share 2019
Provides market share data for many categories of communications semiconductors, including Ethernet products, processors, and FPGAs.

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White Papers

Growing AI Diversity and Complexity Demands Flexible Data-Center Accelerators
AI applications are becoming more diverse, even as models for specific applications rapidly advance. CPUs and GPUs offer the flexibility to handle new models, but they deliver poor throughput or efficiency for real-time inferencing. Purpose-built deep-learning accelerators excel for CNNs but often fare poorly on other model types. SimpleMachines developed a unique “composable computing” architecture that provides both programmability and efficiency.
Mach-NX: The Root of Trusted Systems
Robust system security requires a layered approach, and the root of trust must begin with a secure boot process. Building on its leadership position, Lattice advanced its secure-control platform by introducing the next-generation Mach-NX family. These new devices keep platform security one step ahead of emerging threats while easing customer designs.
Building Better AI Chips
As progressing to 7nm and beyond becomes ever more complex and expensive, GlobalFoundries is taking a different approach to improving performance by enhancing its 12nm node with lower operating voltages and new IP blocks. The changes are particularly effective for AI (neural-network) accelerators. The new 12LP+ technology builds on the success that the foundry’s customers have already achieved in AI acceleration.
Unified Inference and Training at the Edge
As more edge devices add AI capabilities, some applications are becoming increasingly complex. Wearables and other IoT devices often have multiple sensors, requiring different neural networks for each sensor, or they may use a single complex network to combine all the input data, a technique called sensor fusion. Others implement on-device training to customize the application. The GPX-10 processor can handle these advanced AI applications while keeping power to a minimum.
Deterministic Processing for Mission-Critical Applications
Time-sensitive applications such as automotive and robotics require fast and consistent response times. Features such as caches and branch prediction hamper responsiveness. SiFive CPUs can disable these features to deliver deterministic responses. They also combine Linux and RTOS CPUs in the same cluster to enhance responsiveness while offering smaller die area than competitors.
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March 1, 2021

Snapdragon Shifts to Self-Driving Cars
Building on its leadership in automotive connectivity chips (cellular modems and Bluetooth+Wi-Fi combos), Qualcomm is developing Snapdragon-based systems that target ADASs, autonomous vehicles, and cockpit monitoring.
Pixelworks’ i6 Renews Phone Displays
Pixelworks brings premium features to midrange phones by continuously improving images and video to high dynamic range (HDR) and reducing power consumption in certain applications.
Qualcomm Pushes 5G to 10Gbps
The Snapdragon X65 modem increases the top data rate by 33% relative to the older Snapdragon X60. The 4nm design offers a preview of the 5G capabilities in Qualcomm’s next-generation flagship-smartphone processor.

February 22, 2021

Horizon Robotics Plots ADAS Journey
In 2Q21, Horizon Robotics plans to start volume production of its Journey 3 ADAS processor. At the same time, it intends to sample Journey 5, which targets Level 4 autonomous vehicles.
Maxim Showcases Efficient Custom AI
The top-10 microcontroller vendor has hopped on the AI bus with its ultra-low-power MAX78000. The device combines a complete Arm-based MCU with the company’s first deep-learning accelerator (DLA).
Editorial: Gelsinger’s Big Challenge
New Intel CEO Pat Gelsinger, with the help of three trusted lieutenants, must fix the engineering problems that have plagued not just the company’s fab technology but also important server and AI products.

February 15, 2021

Enflame Stokes AI Acceleration
Enflame Technology closed a 1.8-billion-yuan ($280 million) Series C round last month that includes backing from Tencent. The Shanghai startup now offers a series of AI accelerators for both training and inference.
MT8192 Creates Chromebook Buzz
Hoping to steal share from Intel, MediaTek raised its sights in the Chromebook market by delivering the MT8192, doubling CPU performance and tripling GPU performance compared with its predecessor.
Qualcomm Acquires Nuvia for CPUs
Although the startup was developing a custom Arm-compatible CPU core for a new server processor, Qualcomm will redirect this power-efficient core to serve in flagship smartphones and other products.

February 8, 2021

SambaNova Takes On Nvidia’s DGX
The well-funded startup has developed a custom AI-accelerator chip, called the Cardinal SN10, that implements a coarse-grained reconfigurable architecture (CGRA) to handle training and inference.
MediaTek Redefines Premium Phones
The Dimensity 1100 and 1200 target an emerging class of devices for customers who want a great smartphone but don’t want to spend $1,000. The D1200 offers industry-leading multicore performance.

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