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Most Recent Guides & Forecasts

Communications Semiconductor Market Share 2020
Provides market share data for many categories of communications semiconductors, including Ethernet products, processors, and FPGAs.
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.

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White Papers

DPU-Based Hardware Acceleration: A Software Perspective
Data-processing units (DPUs) promise greater data-center efficiency, but low-level-programming requirements have hindered broad adoption. Nvidia aims to remove this obstacle using its DOCA framework, which abstracts the programming of  BlueField DPUs. Furthermore, customers will be able to program future converged DPU+GPU hardware using the combination of DOCA and CUDA.
CertusPro-NX Reinvigorates General-Purpose FPGAs
CertusPro-NX, the fourth product developed using Lattice Semiconductor’s Nexus platform in the last 18 months, delivers class-leading power, performance, and size for diverse applications. These general-purpose FPGAs offer low power, small packages, and high-bandwidth I/Os, such as PCIe Gen3 and Gigabit Ethernet. They’re well suited to edge AI, industrial IoT, 5G control planes, and other tasks.
Chiplets Gain Rapid Adoption: Why Big Chips Are Getting Small
Leading chip vendors such as AMD and Intel have adopted chiplet technology for several products. This technology can reduce cost for large 7nm designs by as much as 25%, according to our analysis; the savings are even greater at 5nm and beyond. We expect chiplets will be widely used for data-center processors and networking chips in these advanced nodes.
Expedera Redefines AI Acceleration for the Edge
Expedera is a small company with big ideas. Rather than optimizing the usual AI techniques, the company rethought neural-network acceleration from the ground up, creating a unique approach that greatly improves performance while maintaining consistent power and die area. This design is well suited to many consumer and automotive applications, enabling customers to increase the intelligence of their devices and add new capabilities to benefit their end users.
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.
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July 26, 2021

Die Photos Show Cortex-A78 Shortfall
Arm’s new CPUs were supposed to bring new efficiencies to smartphone processors, but initial implementations of Cortex-X1 and Cortex-A78 are larger than expected, reducing area efficiency.
Editorial: Huawei Builds New Supply Chain
To combat US sanctions, Huawei is attempting to build an entirely Chinese supply chain by investing in local companies and constructing its own fab. Fully escaping the sanctions, however, will be difficult.

July 19, 2021

Training Competitors Battle on MLPerf
The latest benchmark scores for AI training show that three challengers—Graphcore’s GC200, Habana’s Gaudi, and Huawei’s Ascend—are making progress but still lag Nvidia’s A100 and Google’s TPUv4.
Cadence Floats K-Series DSPs
The new Tensilica KP1, KP6, KQ7, and KQ8 DSPs are optimized for floating-point workloads, offering up to a 40% area reduction and 30% energy savings relative to previous Tensilica DSPs.
Qualcomm Targets 5G Embedded
The four new embedded products target industrial tablets, drones, point-of-sale terminals, kiosks, and similar applications, particularly those that can take advantage of its integrated 5G modem.

July 12, 2021

Marvell Adds Vectors to Octeon 10
The company’s newest data-processing unit (DPU) adds vector packet processing and an AI engine. Marvell expects to sample the first Octeon 10 processors later this year, targeting edge and cloud networking.
NXP S32R Handles Automotive Radar
The new chips address the entire range of automotive-radar applications from ADAS to self-driving cars. They include the S32R294 microcontroller, S32R45 imaging-radar processor, and TEF82xx transceivers.
ProteanTecs Aids in Manufacturing
Startup ProteanTecs licenses its Universal Chip Telemetry platform, which combines AI models and a collection of sensors, to reduce chip defect rates by 10x and to cut manufacturing costs.

July 5, 2021

P550 Doubles Floating-Point Capability
After picking up new customers Renesas and Tenstorrent, SiFive released two new CPU cores: the P270 and P550. These offerings sit atop the product stack, targeting Linux-based application processors.
Data Centers Drive to 800Gbps Optics
At the recent Optical Fiber Communication Conference (OFC), Broadcom, Marvell, and MaxLinear announced 112Gbps PAM4 physical-layer chips, including the first built in 5nm technology.
Quadric’s Flexible Edge Accelerator
Startup Quadric is now sampling its first chip, a data-flow processor that can handle a range of tasks from signal processing to AI. The 256-core design consumes less than 4W and targets edge applications.

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Linley Fall Processor Conference 2021
Coming October 20-21, 2021
Hyatt Regency Hotel, Santa Clara, CA
Linley Spring Processor Conference 2021
April 19 - 23, 2021
Proceedings Available
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