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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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January 18, 2021

Year in Review: Smartphone Chips Get Bigger GPUs
Smartphone shipments cratered in 2020, but 5G was a bright spot. The popularity of inexpensive 5G phones pushed MediaTek to the top position in processor sales. GPUs and AI grew in importance.
Xsight Samples Leading-Edge Switch
Led by a highly successful team, the Israeli startup emerged from stealth last month and announced its first chip, called the X1.
Editorial: Smart Speakers Get AI Edge
The newest devices from Amazon, Apple, and Google include AI engines that enable them to process some voice commands in the device rather than in the cloud and to perform other new functions.

January 11, 2021

Apple Ships Its First PC Processor
The M1 processor sets new standards for laptop performance and battery life. The chip shares much of its design with the A14 smartphone processor, including its powerful Firestorm and Icestorm CPUs.
Year in Review: PC Processors Bounce Back
In 2020, PC shipments surged, AMD topped PC performance, Nvidia’s Ampere GPU impressed, Intel revived its laptop lineup, Apple’s M1 doubled battery life, and two new game consoles debuted.
Broadcom SmartToR Ups Flow Scale
Broadcom announced three new data-center switch chips in December as well as production of its original Tomahawk 4. The new Trident SmartToR is an 8.0Tbps switch that builds on the 7nm Trident 4 architecture.

January 4, 2021

Year in Review: IP Adapts to Automotive Roadmap
The latest CPU, deep-learning-accelerator (DLA), DSP, and GPU cores improve safety and performance in vehicles. IP vendors also launched new DLAs that address a broad range of applications.
SimpleMachines Enables Flexible AI
Startup SimpleMachines received first silicon of its Mozart inference chip, which approaches the flexibility of a GPU while promising the performance of a purpose-built deep-learning accelerator (DLA).
SiFive Brings Vectors to S-Series
SiFive’s newest RISC-V vector core, the VIS7, can perform 64 gigaflop/s and is designed for deterministic operations. In addition, the new 20G1 release improves 7-series performance and frequency.

December 28, 2020

Year in Review: Data-Center Silicon Diversifies
Following a difficult 2019, the data-center-chip market had a surprisingly great 2020. AMD and Nvidia delivered important new devices, whereas Intel struggled to execute. More AI startups released products, and Qualcomm’s looming entry could upset the market.
Exynos 1080 Doubles GPU Throughput
The Exynos 1080 is Samsung’s newest mid-premium smartphone SoC. By shifting to the company’s 5nm LP technology, it boosts performance across the board relative to the older Exynos 980.

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Linley Fall Processor Conference Proceedings

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Analysis of new developments in microprocessors and other semiconductor products
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Linley Spring Processor Conference 2021
Coming the week of April 19, 2021
Virtual Event
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