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Raspberry Pi Compute Module 4 vs Radxa CM3: A Technical Comparison for Industrial Automation

Industrial automation is a rapidly growing field that relies on powerful and efficient computing platforms to control and monitor complex processes. Two popular options for industrial automation applications are the Raspberry Pi Compute Module 4 and the Radxa CM3. In this article, we will compare the technical features of these two boards and discuss their suitability for industrial automation.

CM4 vs CM3?

The Raspberry Pi Compute Module 4 is equipped with a quad-core Cortex-A72 CPU clocked at up to 1.5GHz. The Cortex-A72 is a high-performance core that is ideal for applications that require a lot of computational power, such as machine learning and computer vision.

On the other hand, the Radxa CM3 is powered by the Rockchip RK3566 processor, which features four Cortex-A55 cores clocked at up to 2.0GHz. While the Cortex-A55 is not as powerful as the Cortex-A72, it is designed for power efficiency, making it a better option for battery-powered devices or IoT applications.

What about the memory?

The Raspberry Pi Compute Module 4 is available in several configurations, ranging from 1GB to 8GB of LPDDR4 RAM. It also features an optional 8GB, 16GB, or 32GB eMMC flash storage.

The Radxa CM3, on the other hand, comes with 2GB or 4GB LPDDR4 RAM, and 16GB or 32GB eMMC flash storage. While the Raspberry Pi Compute Module 4 offers more RAM options, the Radxa CM3 comes with more eMMC storage options.

Which module comes best in terms of features?

The Raspberry Pi Compute Module 4 offers a wide range of connectivity options, including dual-band 2.4GHz and 5GHz Wi-Fi, Bluetooth 5.0, Gigabit Ethernet, and PCI Express 2.0. The Radxa CM3 features dual-band 2.4GHz and 5GHz Wi-Fi, Bluetooth 5.0, and Gigabit Ethernet.

Both the Raspberry Pi Compute Module 4 and the Radxa CM3 come with features that are useful for industrial automation applications. For example, they both offer long-term availability, support for industrial temperature ranges, and high reliability. However, the Raspberry Pi Compute Module 4 offers some additional features that may be useful for industrial applications, such as support for dual display output and a wider range of peripherals.

In conclusion, the Raspberry Pi Compute Module 4 and the Radxa CM3 are both powerful and efficient computing platforms that are well-suited for industrial automation applications. The Raspberry Pi Compute Module 4 is better suited for applications that require high computational power, while the Radxa CM3 is better suited for applications that require power efficiency. Ultimately, the choice between these two boards will depend on the specific needs of the industrial automation application in question.

ModBerry R1 industrial supply

The ModBerry R1 is available to order from several online retailers, and it is a cost-effective alternative to the Raspberry Pi Compute Module 4. With its compact size and powerful hardware, the ModBerry R1 is a great solution for users who need a single-board computer for their projects. Whether you are building an industrial control system, a home automation system, or a media center, the ModBerry R1 is an excellent choice.

Raspberry Pi Compute Module 4 scarcity has created an opportunity for alternatives to emerge, and the ModBerry R1 with Radxa CM3 is one such alternative. With its powerful hardware and compatibility with the Raspberry Pi, the ModBerry R1 is a cost-effective solution for users who need a single-board computer for their projects. If you are looking for a powerful and versatile single-board computer, the ModBerry R1 is definitely worth considering.

The Raspberry Pi Compute Module 4 (CM4) has been in high demand since its release in 2020, due to its powerful hardware and versatility as a single-board computer. The CM4 has been used in a wide range of applications, from industrial control systems to media centers and home automation systems. However, the high demand for the CM4 has resulted in a scarcity of the device, making it difficult for many users to get their hands on one.

Low supply, high demand

To address the issue of low supply, several companies have started offering alternatives to the Raspberry Pi Compute Module 4. One such alternative is the ModBerry500 R1, which is based on the Radxa CM3. The ModBerry 500 R1 is a compact and versatile single-board computer that provides many of the same capabilities as the Raspberry Pi CM4. It features a powerful quad-core Arm Cortex-A53 processor and variety of RAM/eMMC options, making it suitable for a wide range of applications.

The Radxa CM3, which is the heart of the ModBerry 500 R1, is a highly integrated computer-on-module that combines a powerful processor, RAM, and storage in a compact package. The CM3 is fully compatible with the Raspberry Pi, which means that users can use the same software and accessories as they would with a Raspberry Pi. This makes it an ideal solution for users who want the power and versatility of the Raspberry Pi, but cannot get their hands on a CM4 due to its scarcity.

ModBerry R1 industrial supply

The ModBerry R1 is available to order from several online retailers, and it is a cost-effective alternative to the Raspberry Pi Compute Module 4. With its compact size and powerful hardware, the ModBerry R1 is a great solution for users who need a single-board computer for their projects. Whether you are building an industrial control system, a home automation system, or a media center, the ModBerry R1 is an excellent choice.

Raspberry Pi Compute Module 4 scarcity has created an opportunity for alternatives to emerge, and the ModBerry R1 with Radxa CM3 is one such alternative. With its powerful hardware and compatibility with the Raspberry Pi, the ModBerry R1 is a cost-effective solution for users who need a single-board computer for their projects. If you are looking for a powerful and versatile single-board computer, the ModBerry R1 is definitely worth considering.

The Raspberry Pi Compute Module is a small form-factor computer that has been designed for use as an embedded device. The latest version of the Compute Module is the Raspberry Pi Compute Module 4, which was released in June 2020.

It is likely that the next iteration of the Raspberry Pi Compute Module will feature improved performance and updated components, while retaining the small form factor and low power consumption that have made the Compute Module popular. This might include the latest generation of processors and memory, as well as improved connectivity options and expanded storage capabilities.

Additionally, the Raspberry Pi Foundation has a history of releasing new Compute Module versions every two to three years, so it is possible that the next Compute Module could be released sometime in 2023 or 2024. Overall, the Raspberry Pi Compute Module continues to evolve and improve, offering a compact and versatile platform for a wide range of embedded computing applications. Stay tuned for future updates from the Raspberry Pi Foundation.

Current version of Raspberry Pi Compute Module 4

Possible feature and specs changes

It is difficult to predict the exact specifications of a future Raspberry Pi Compute Module, as these are subject to change based on various factors, including advancements in technology and market demands. However, based on the current trends and recent releases, the next Compute Module might feature:

  • Processor: The next Compute Module might feature a more powerful processor, such as a newer generation of ARM-based chips or even a custom chip designed specifically for the Raspberry Pi. The processor might have improved performance and power efficiency, providing a faster and more efficient computing experience.
  • Memory: The next Compute Module might come with increased memory options, such as LPDDR5 RAM or larger capacity options, providing more room for larger applications and multiple tasks.
  • Connectivity: The next Compute Module might have improved connectivity options, such as faster Ethernet, Wi-Fi 6 support, or 5G connectivity. This would make the device better suited for applications that require a fast and reliable internet connection.
  • Storage: The next Compute Module might feature expanded storage options, such as larger eMMC storage or support for NVMe SSDs, providing more room for data storage and enabling faster read and write speeds.
  • Other features: The next Compute Module might also include other features and improvements, such as improved thermal management, support for more displays or cameras, or a more compact form factor.

These are just some of the potential improvements that the next Raspberry Pi Compute Module might feature. It is important to note that these are only speculations and actual specifications may differ. But before CM5 will see the light of day, meet ModBerry 500 CM4 & and it’s cousing ModBerry 500 R1, powered by Radxa CM3.

ClusBerry is a cluster of Raspberry Pi computers developed by TECHBASE. The cluster is made up of multiple Raspberry Pi Compute Module 4’s that are connected together, allowing them to work together to perform tasks that would otherwise be too computationally intensive for a single board. This makes ClusBerry a powerful, low-cost solution for parallel computing and high-performance computing applications.

One of the key features of ClusBerry is its flexibility. The cluster can be configured with a variety of different types of Raspberry Pi-like modules, including the Raspberry Pi Compute Module 4 and latest Radxa CM3. This allows users to choose the configuration that best meets their needs in terms of performance, cost, and power consumption.

ClusBerry device fitted with Software

Another important feature of ClusBerry is its software stack. The cluster is pre-installed with a range of software tools and libraries that are commonly used in parallel computing and high-performance computing applications. This includes tools for job scheduling, resource management, and data transfer, as well as libraries for machine learning, data processing, and scientific simulations.

ClusBerry can be used for a variety of applications, including machine learning, data processing, and scientific simulations. For example, it can be used to train large machine learning models, process large datasets, or run complex simulations. Some of the specific use cases that ClusBerry can be applied to include:

  • Image and video processing: ClusBerry can be used to process large amounts of image and video data, such as in the field of computer vision.
  • Machine learning: ClusBerry can be used to train large machine learning models, such as deep learning models, using parallel computing techniques.
  • Scientific simulations: ClusBerry can be used to run complex simulations in fields such as physics, chemistry, and biology.
  • Data processing: ClusBerry can be used to process large amounts of data, such as in the field of big data.

Overall, ClusBerry is a powerful and flexible solution for parallel computing and high-performance computing applications. Its low cost, ease of use, and wide range of software tools and libraries make it well-suited for a wide range of use cases.

Small CM4 cluster in ClusBerry-2M

The introduction of new Compute Module 4 has opened the possibility to construct and maintain effective hardware matrix solutions with the use of both PCI-Express buses and 1GBps Ethernet. Therefore, the ClusBerry-2M opens up completely new capabilities of utilizing cluster solutions for Industrial Automation and server applications.

ClusBerry-2M can be equipped with multiple expansion cards, e.g. serial RS-232/485 ports, range of digital and analog I/Os, USB, HDMI and Ethernet. Interfaces can be expanded with additional I/Os and opto-isolation, relays, Ethernet, 1-Wire, CAN, M-Bus Master and Slave, accelerometer and many more features like TPM Security Chip & eSIM. The device can also be equipped with additional SuperCap backup power source for continuous work and safe boot/shutdown in case of emergency.

ClusBerry-2M series also offers two M.2 NVMe SSD slots and up to four standard miniPCIe module support for various wireless communication protocols, such as:

  • GSM modem (4G/LTE and fast 5G modem)
  • economic NarrowBand-IoT technology
  • LoRa, ZigBee, Z-Wave, Sigfox, Wireless M-Bus
  • secondary Wi-Fi/Bluetooth interface or Wi-Fi Hi-Power
  • custom wireless interfaces

Software cluster management with Docker and K3s Lightweight Kubernetes

With use of Docker-based and Kubernetes solutions, installation and management of ClusBerry-2M is easy and backed with a large community for further support and development. Kubernetes is a portable, extensible open-source software platform for managing containerized tasks and sites that enables declarative configuration and automation. The Kubernetes ecosystem is large and dynamically developing. Kubernetes services, support and tools are widely available.

Kubernetes provides:

  • Detection of new services and traffic. Kubernetes can balance the load and redirect the network traffic to ensure the stability of the entire installation.
  • Kubernetes data storage management enables you to automatically mount any type of storage system – on-premises, from cloud providers and others.
  • Automatic deployment and rollback. You can describe the expected state of your installation with Kubernetes, which will take care of bringing the actual state to the expected state in a controlled manner. For example, with Kubernetes, you can manage your cluster modules at ease, boot modules from one to another, upgrade firmware crosswise and provide safe operation of each module.
  • Automatic management of available resources. ClusBerry-2M provides a cluster of modules that Kubernetes can use to run tasks in containers. You determine the CPU power and RAM requirements for each container. Kubernetes arranges containers on machines in such a way as to make the best use of provided resources.
  • Self-healing Kubernetes reboots containers that have stopped working, replaces them with new ones, forces disabling containers that are not responding to certain status queries, and does not announce their availability until they are ready to run.
  • Managing confidential information and Kubernetes configuration with TPM Security Chip allows you to store and manage confidential information such as passwords, OAuth tokens and SSH keys. Secured data and configuration information can be provided and changed without having to rebuild the container image and without exposing sensitive data in the overall software configuration.

ClusBerry-2M availability

Basic version of ClusBerry-2M is available in 2-4 weeks. Delivery time for various configurations of ClusBerry-2M including ExCard modules and modems can be approximately 2 months, depending on the CM4 supply on the market and chosen expansion cards. For more information please contact via our website and sign the offer here: https://clusberry.techbase.eu/