Communications Semiconductor Market Share 2019
Provides market share data for many categories of communications semiconductors, including Ethernet products, processors, and FPGAs.
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.
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 2018–2023
Provides five-year revenue forecasts for more than 20 categories of communications semiconductors, including Ethernet products, broadband interface chips, embedded processors, server processors and FPGAs.
Provides five-year revenue forecasts for more than 20 categories of communications semiconductors, including Ethernet products, broadband interface chips, embedded processors, server processors and FPGAs.
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
Machine Learning Moves to the Edge
Embedded systems at the edge of the network will increasingly use machine learning (ML) to deliver new capabilities. Even as ML becomes more important, these new capabilities must be added without breaking the BOM cost and power budgets of existing products. The best option is an SoC that includes the CPU, standard interfaces, and an efficient ML accelerator on a single chip, minimizing cost, power, and board area. SiMa.ai is a new company developing a product to fit these requirements.
Embedded systems at the edge of the network will increasingly use machine learning (ML) to deliver new capabilities. Even as ML becomes more important, these new capabilities must be added without breaking the BOM cost and power budgets of existing products. The best option is an SoC that includes the CPU, standard interfaces, and an efficient ML accelerator on a single chip, minimizing cost, power, and board area. SiMa.ai is a new company developing a product to fit these requirements.
Accelerating AI Performance in an Open Software Ecosystem
Nvidia's software stack, based on its proprietary CUDA, creates a high barrier to entry for challengers. SYCL, the only open alternative to CUDA that has multivendor support, enables customers to move to higher performance hardware while retaining software flexibility. A commercial version of SYCL, branded ComputeCpp, is offered by Codeplay.
Nvidia's software stack, based on its proprietary CUDA, creates a high barrier to entry for challengers. SYCL, the only open alternative to CUDA that has multivendor support, enables customers to move to higher performance hardware while retaining software flexibility. A commercial version of SYCL, branded ComputeCpp, is offered by Codeplay.
Arm Ecosystem Reduces SoC Design Cost and Time to Market
This paper discusses three critical facets of the Arm ecosystem: design verification, physical design, and software development. Each one directly affects the time required to develop a complete SoC and software stack.
This paper discusses three critical facets of the Arm ecosystem: design verification, physical design, and software development. Each one directly affects the time required to develop a complete SoC and software stack.
AI Requires Many Approaches
Artificial intelligence (AI) is being applied to a wide range of problems, so no single processor can support them all. This paper describes and compares the various approaches needed for data center, autonomous driving, and consumer/IoT applications.
Artificial intelligence (AI) is being applied to a wide range of problems, so no single processor can support them all. This paper describes and compares the various approaches needed for data center, autonomous driving, and consumer/IoT applications.
