top of page

Leon County Democrat Group

Public·11 members
Wyatt Reed
Wyatt Reed

Processors For Internet Of Things __HOT__


The company made the announcement at the start of its ARM TechCon event in Santa Clara, Calif. The M23 and M33 are the first in a new family of ARMv8 processors that incorporate the ARM TrustZone technology for better hardware security, said Michael Horne, vice president of marketing and sales in the IoT business group at ARM, in a press briefing. The designs make it easier for developers to create energy-efficient, secure, and connected IoT devices.




Processors for Internet of Things


Download File: https://www.google.com/url?q=https%3A%2F%2Furluso.com%2F2u7ewS&sa=D&sntz=1&usg=AOvVaw26TrzzKHYskF-MzxToZwI7



Ten of the biggest microcontroller manufacturers have licensed the processors from ARM. Announced chip partners include Analog Devices, Microchip, Nuvoton, NXP, Renesas, Silicon Labs, and STMicroelectronics.


Most chip designs have trade-offs when it comes to efficiency, security, cost, and performance. But ARM has tried to consider all of these factors in designing the small, balanced chips that will serve as the brains of a lot of smart objects, Horne said. Applications for the processors vary widely and include remote health monitoring, smart lighting, streamlining logistics, and managing flood defenses.


For IoT to reach its potential, its foundation must be based on proven and trusted technology. The first Cortex-M processors, based on the ARMv8-M architecture with TrustZone technology, are based on 32-bit computing. The Cortex-M33 is 20 percent faster than past models, the Cortex-M3 and the Cortex-M4, and the M33 has better power efficiency.


Enhanced for IoT processors deliver intelligent workload optimization with performance hybrid architecture for superior single-thread and multithread performance, combining Performance-cores (P-cores) and Efficient-cores (E-cores).


Ideal for video analytics, workload consolidation, and other demanding applications, these processors deliver server-class computing, hardware-based security, and high-bandwidth I/Os for embedded and rugged applications.


This ever-increasing demand for smaller devices with more functionality, longer battery life, and shorter time-to-market has accelerated the need for a new breed of low-power embedded processors and subsystems. Standard and general-purpose processors are less and less suited to the demands of these kinds of applications.


The configurable and extensible ARC EM4 Processor, with its lower power, higher performance efficiency than competing 32-bit processor cores, configurability, and extensibility, is an example of the new breed of processors that is needed to better meet the needs of these demanding applications.


Designers also can select an ultra-low-power processor and a package with lower thermal resistance. Additionally, they can improve the power dissipation capability of the package by using heat sinks or air circulation, but things get more challenging when the processor is inside a sealed casing.


The CRC algorithm provides a workload commonly seen in embedded applications and ensures correct operation of the CoreMark benchmark, essentially acting as a self-checking mechanism. This process performs a 16-bit CRC on the data contained in elements of the linked list to verify correct operation. The system is designed to run on devices from eight-bit microcontrollers to 64-bit microprocessors.


11th Gen Intel Core processors for IoT are enhanced specifically for essential internet of things applications that require high-speed processing, computer vision and low latency deterministic computing. They were introduced in September 2020. (Credit: Intel Corporation)


About 11th Gen Core Processors: Building on the recently announced client processors, 11th Gen Core is enhanced specifically for essential IoT applications that require high-speed processing, computer vision and low-latency deterministic computing. It delivers up to a 23% performance gain in single-thread performance, a 19% gain in multithread performance and up to a 2.95x performance gain in graphics gen on gen.3 New dual-video decode boxes allow the processor to ingest up to 40 simultaneous video streams at 1080p 30 frames per second and output up to four channels of 4K or two channels of 8K video. AI-inferencing algorithms can run on up to 96 graphic execution units (INT8) or run on the CPU with vector neural network instructions (VNNI) built in. With Intel Time Coordinated Computing (Intel TCC Technology) and time-sensitive networking (TSN) technologies, 11th Gen processors enable real-time computing demands while delivering deterministic performance across a variety of use cases:


More Context: 12th Gen Intel Core processors for IoT Edge The Industries of the Future Rely on Graphics, Adaptability and Manageability Today (Alec Gefrides Blog) 12th Gen Intel Core processors for IoT Edge (Product Brief)


The 11th Gen Intel Core & Intel Atom x6000E Series processors aim to bring more compute to edge applications. The company also outlined an Edge Software Hub including use-case specific reference designs, customization tools and reusable container packages for retail, industrial, predictive analytics, and computer vision.


Intel is aiming to create an ecosystem for industrial IoT, which will be enabled by 5G. Qualcomm launched edge computing processors and hardware reference designs with its 5G connectivity. Intel's play will be more about private 5G deployments as well as public network use.


While it is possible to implement an Internet enabled embedded system using various types of processor architectures, some processor architectures are better than others in such application areas. In this paper we will analyse how the ARM Cortex-M processors match the requirements of IoT scenarios, what we are doing to support the necessary software development and the challenges in achieving wider IoT deployment.


While currently many Internet enabled embedded systems are implemented with application processors such as the ARM Cortex-A processors, ARM11 processors or x86 architecture, we will be focusing on low cost microcontrollers in this paper because eventually, when the IoT market takes off, most of the IoT enabled devices will be based on low cost microcontrollers rather than application processors.


Background of the Cortex-M processorsThe ARM Cortex-M3 processor was the first product to be developed in the Cortex-M processor family. Microcontrollers based on the Cortex-M3 were first released in 2006, and now there are five processors in the Cortex-M processor family, with 12 microcontroller vendors supplying microcontrollers based on the Cortex-M processors and thousands of devices available.


Different Cortex-M processor products support different ranges of instruction set. The Cortex-M0, Cortex-M0+ and Cortex-M1 processors are all based on the ARMv6-M architecture. The Cortex-M3 and Cortex-M4 are based on ARMv7-M architecture, which has a larger instruction set.


For general data processing and normal I/O control tasks, the ARMv6-M architecture is sufficient and provides the best energy efficiency. For more complex data handling, the processors from the ARMv7-M architecture such as the Cortex-M3 provide additional instructions which accelerate data processing, as well as providing additional instructions for hardware divide, bit field processing and Multiply-Accumulate (MAC). In more demanding data processing applications like Digital Signal Processing (DSP), the Cortex-M4 processor provides further instructions such as SIMD to enhance DSP performance. Some of the Cortex-M4 devices also include a floating point unit (i.e. Cortex-M4F) which provides optimized single precision floating calculation in the floating point hardware.


The Internet of Things (IoT) is defined as a paradigm in which objects equipped with sensors, actuators, and processors communicate with each other to serve a meaningful purpose. In this paper, we survey state-of-the-art methods, protocols, and applications in this new emerging area. This survey paper proposes a novel taxonomy for IoT technologies, highlights some of the most important technologies, and profiles some applications that have the potential to make a striking difference in human life, especially for the differently abled and the elderly. As compared to similar survey papers in the area, this paper is far more comprehensive in its coverage and exhaustively covers most major technologies spanning from sensors to applications.


For this intelligence and interconnection, IoT devices are equipped with embedded sensors, actuators, processors, and transceivers. IoT is not a single technology; rather it is an agglomeration of various technologies that work together in tandem.


Now, after processing the received data, some action needs to be taken on the basis of the derived inferences. The nature of actions can be diverse. We can directly modify the physical world through actuators. Or we may do something virtually. For example, we can send some information to other smart things.


In particular, we have been slightly vague about the nature of data generated by IoT devices, and the nature of data processing. In some system architectures the data processing is done in a large centralized fashion by cloud computers. Such a cloud centric architecture keeps the cloud at the center, applications above it, and the network of smart things below it [9]. Cloud computing is given primacy because it provides great flexibility and scalability. It offers services such as the core infrastructure, platform, software, and storage. Developers can provide their storage tools, software tools, data mining, and machine learning tools, and visualization tools through the cloud.


We shall subsequently look at two kinds of software components: middleware and applications. The middleware creates an abstraction for the programmer such that the details of the hardware can be hidden. This enhances interoperability of smart things and makes it easy to offer different kinds of services [20]. There are many commercial and open source offerings for providing middleware services to IoT devices. Some examples are OpenIoT [21], MiddleWhere [22], Hydra [23], FiWare [24], and Oracle Fusion Middleware. Finally, we discuss the applications of IoT in Section 9. We primarily focus on home automation, ambient assisted living, health and fitness, smart vehicular systems, smart cities, smart environments, smart grids, social life, and entertainment.


About

Welcome to the group! You can connect with other members, ge...

Members

  • C
    chair308
  • Luca Jackson
    Luca Jackson
  • P
    priceminthelp
  • Alexander Price
    Alexander Price
  • Kai Hernandez
    Kai Hernandez
bottom of page