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.
Most Recent Guides & Forecasts
Communications Semiconductor Market Share 2019
Provides market share data for many categories of communications semiconductors, including Ethernet products, processors, and FPGAs.
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.
Covers processors for accelerating deep learning, neural networks, and vision processing for AI training and inference in data centers, autonomous vehicles, and client devices.
A Guide to Multicore Processors
Covers 32- and 64-bit embedded processors with four or more CPU cores that are used for wires and wireless communications, storage, security, and other applications.
Covers 32- and 64-bit embedded processors with four or more CPU cores that are used for wires and wireless communications, storage, security, and other applications.
A Guide to Ethernet Switch and PHY Chips
Covers data-center switch chips for 10G, 25G, 40G, 50G, and 100G Ethernet. Also includes physical-layer (PHY) chips for 10GBase-T and 100G Ethernet.
Covers data-center switch chips for 10G, 25G, 40G, 50G, and 100G Ethernet. Also includes physical-layer (PHY) chips for 10GBase-T and 100G Ethernet.
A Guide to Processors for IoT and Wearables
Covers processors and connectivity chips for IoT clients and wearable devices, focusing primarily on single-chip solutions with integrated radios.
Covers processors and connectivity chips for IoT clients and wearable devices, focusing primarily on single-chip solutions with integrated radios.
White Papers
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.
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.
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.
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.
C-V2X Drives Intelligent Transportation
This white paper describes the benefits that cellular vehicle-to-everything (C-V2X) technology will provide by enabling vehicles to communicate directly with each other (V2V), transportation infrastructure (V2I), and network-connected service providers (V2N).
This white paper describes the benefits that cellular vehicle-to-everything (C-V2X) technology will provide by enabling vehicles to communicate directly with each other (V2V), transportation infrastructure (V2I), and network-connected service providers (V2N).
