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Raspberry Pi Computer Module 4 (CM4) clones and alternatives

Raspberry Pi Computer Module 4 (CM4) clones and alternatives

In the dynamic world of compact computing, the System on Module (SoM) technology has taken center stage, with the Raspberry Pi Compute Module 4 (CM4) playing a crucial role in the development of tailored computing solutions. The CM4’s design, which omits standard interfaces like USB and HDMI, necessitates the use of carrier boards to unlock its full potential. After facing significant supply issues since early 2021, the CM4 is making a comeback, much to the delight of developers and tech enthusiasts.

The scarcity of CM4s has led to the rise of alternative boards, often referred to as CM4 clones. These clones are compact computers that serve a wide range of uses, from gaming emulators to smart lighting and industrial controls. It’s important to note that these clones are not carbon copies of the original CM4. They often feature different chips and additional functionalities, which can lead to compatibility concerns and booting problems.

Raspberry Pi Computer Module 4 (CM4) alternatives

When evaluating CM4 clones, it’s essential to consider their performance and compatibility. Each clone has its own set of features and strengths, and while some may excel in certain areas, they might fall short in others. Conducting a thorough performance review and compatibility assessment is crucial to ensure that the clone you choose meets the specific needs of your project.

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Looking ahead to 2024, we’re on the brink of seeing some exciting projects come to fruition. The field of industrial touchscreen computers is advancing, and an inventive TV stick adapter for the CM4 is in the works, promising to expand the versatility of your setups. Additionally, specialized flashing tools are being developed to streamline the programming of CM4s.

In the realm of industrial computing, advancements in automation and remote sensing are noteworthy. A particularly impressive innovation is the Pi KVM box, now equipped with USB-C connectivity, which simplifies power and networking arrangements for managing servers remotely.

Despite these advancements, there are concerns about some organizations not adhering to open-source licenses. Maintaining the integrity of the open-source community by respecting these licenses is vital, as they are foundational to much of the innovation in this field.

CM5

There’s also growing speculation about the potential release of a Compute Module 5. While details are still under wraps, the community is buzzing with excitement, eagerly awaiting updates that are expected to come out in the first half of 2024. As always we will keep you up to speed as any new information, specifications or news is released. In the meantime the Raspberry Pi Computer Module 4 is available to by from a number of worldwide resellers.

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Raspberry Pi 5 NVMe SSD storage using the HATDrive Top

Raspberry Pi 5 NVMe SSDs using the HATDrive Top Edition and BM1

If you are looking to add faster,  more reliable or simply just extra storage to your new Raspberry Pi 5 mini PC you will be pleased to know that Pi  enthusiast Jeff Geerling has created a great video showing you how easy it is using the Pineberry Pi HatDrive. The Raspberry Pi 5 expansion board has been designed to provide optimal airflow, together with easy access to GPIO expansion, securely mounts underneath the board and is compatible with NVMe drives up to 2280.

For enthusiasts and semi-technical users alike, the introduction of Raspberry Pi NVMe SSD HATs, such as the HatDrive Top Edition and HatDrive BM1 by Pineberry Pie, is an exciting development. These devices tap into the Raspberry Pi 5’s PCI Express interface, offering a significant boost in storage performance compared to traditional micro SD cards. This guide will walk you through the process of supercharging your Raspberry Pi with these innovative storage solutions.

The Raspberry Pi 5 is a versatile and compact computer that has captured the imagination of hobbyists and professionals around the world. With the release of the HatDrive Top Edition and HatDrive BM1, users can now easily enhance their Raspberry Pi’s storage capabilities. These HATs connect through the PCI Express interface, a feature that marks a significant step forward in storage technology for the Raspberry Pi. By upgrading to an NVMe SSD, you’ll not only expand your device’s storage capacity but also enjoy faster data transfer rates, which can streamline your projects and workflows.

Advantages of SSD’s over SD cards

The advantages of NVMe SSDs over micro SD cards are clear. NVMe technology offers superior read/write speeds, which translates to quicker boot times for your Raspberry Pi OS and faster data access. This speed is particularly beneficial for applications that require quick data retrieval, such as media servers or file storage solutions. The NVMe SSDs, when paired with the Raspberry Pi 5, provide a noticeable improvement in performance, making them an attractive option for users looking to push their devices further.

  • Faster Read/Write Speeds: SSDs provide significantly faster data transfer rates compared to SD cards. This speed boost enhances overall system performance, leading to quicker boot times, faster file transfers, and more responsive applications.
  • Greater Durability: SSDs have no moving parts, making them more resistant to physical shock and less prone to mechanical failure. This makes them a more robust option for projects that might involve movement or less stable environments.
  • Longer Lifespan: SSDs generally have a longer lifespan than SD cards. They can handle more read/write cycles before failure, which is crucial for applications that involve frequent data writing.
  • Higher Capacity Options: SSDs are available in larger capacities than SD cards, allowing for more storage space for applications, data, and files. This is particularly useful for data-intensive projects or media storage.
  • Better Reliability: SSDs tend to be more reliable over time. SD cards, especially lower-quality ones, are more susceptible to corruption and data loss over extended periods of heavy use.
  • Improved Heat Management: While SSDs can generate more heat than SD cards, they are also better equipped to handle it. This can result in more stable performance under load, assuming proper thermal management is in place.
  • Enhanced Data Security: Some SSDs come with built-in encryption capabilities, offering better data security than standard SD cards. This is beneficial for sensitive data storage.

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Raspberry Pi 5 SSD setup

The PCI Express interface on the Raspberry Pi 5 is not just for storage; it opens the door to a range of enhancements. This versatile connection allows users to explore various PCI Express-compatible devices, potentially adding new functionalities to their Raspberry Pi setup. To begin your upgrade, you’ll need to flash the Raspberry Pi OS onto your NVMe SSD. Following a detailed setup guide for the Raspberry Pi NVMe SSD will help ensure a smooth transition. Once the OS is installed, booting from the NVMe SSD is a simple process, provided you adhere to the correct instructions.

After installing the operating system, the next step is to configure the software settings. It’s crucial to adjust the Raspberry Pi settings to recognize the NVMe SSD as the primary boot device. This step is essential in the configuration process and ensures that your Raspberry Pi utilizes the full potential of the NVMe SSD. A robust power supply is vital for this upgrade. NVMe SSDs consume more power than micro SD cards, so it’s important to ensure that your power adapter can handle the increased demand. This will help prevent any power-related issues that could affect performance or cause system instability.

Once your system is up and running, it’s time to benchmark the performance of your Raspberry Pi with the new NVMe SSD. Benchmarking will provide you with concrete data on the speed improvements and help you optimize your setup further. You’ll be able to see firsthand the performance gains that come with this storage upgrade.

Compatibility, power and reliability

But it’s not just about speed. NVMe SSDs are also built to last. With no moving parts inside, they are less prone to mechanical failure compared to traditional hard drives. This makes them an excellent choice for projects where reliability is paramount, such as in situations where the Raspberry Pi is part of a larger, mission-critical system.

However, as with any technological upgrade, there are practicalities to consider. Not all Raspberry Pi models are ready to work with NVMe SSDs out of the box. Depending on your model, you might need additional hardware, like an NVMe to USB adapter or a specialized expansion board (often referred to as a HAT), to make the connection possible. This not only adds to the cost but also to the complexity of your setup.

Another consideration is power. NVMe SSDs are more power-hungry than their SATA counterparts. This could be a stumbling block if your Raspberry Pi project is battery-powered or if you’re trying to keep energy consumption to a minimum. It’s a trade-off between the performance benefits and the practical aspects of power supply and hardware compatibility.

Cooling your Pi SSD

With enhanced performance comes increased heat generation, making effective thermal management essential. NVMe SSDs typically operate at higher temperatures than micro SD cards. Therefore, it is important to ensure that your Raspberry Pi 5 case is equipped with sufficient ventilation to maintain safe operating temperatures. Adequate thermal management is crucial to prevent overheating and to ensure the durability of your device.

Before initiating this upgrade, confirming the compatibility of your NVMe SSD with the Raspberry Pi is vital. Not every NVMe SSD is compatible with all HAT devices. Thus, conducting prior research is imperative. This ensures that the SSD you select operates as intended and helps avoid potential disappointment.

By integrating an NVMe SSD into your Raspberry Pi 5 with a HAT device like those offered by Pineberry Pie, you’ll enjoy faster boot times, quicker data transfers, and improved reliability. This guide aims to ensure that you have a smooth installation and configuration process, allowing you to unlock the full capabilities of your Raspberry Pi 5. With this upgrade, your Raspberry Pi will be better equipped to handle demanding applications, making it a more powerful tool in your tech arsenal. Whether you’re a hobbyist looking to experiment with new projects or a professional seeking to optimize your workflow, the addition of an NVMe SSD to your Raspberry Pi 5 is a step toward enhanced computing performance.

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CaribouLite converts your Raspberry Pi into an open source radio

CaribouLite HAT converts your Raspberry Pi into an open source radioTransform your Raspberry Pi into a powerful tool for radio communication, capable of exploring frequencies that stretch up to an impressive 6 GHz. The CaribouLite Raspberry Pi radio HAT makes this possible, offering a dual-channel software-defined radio (SDR) platform that’s both versatile and affordable. This innovative accessory is designed for hobbyists, educators, and researchers who are passionate about radio exploration and innovation.

The CaribouLite stands out with its dual-channel functionality, allowing users to receive and transmit on two different frequencies at the same time. This is particularly useful for complex radio operations, such as managing cross-band repeaters or monitoring multiple bands simultaneously. It’s a significant advantage for those who are serious about their radio projects and are looking for more sophisticated capabilities.

CaribouLite RPi HAT

By leveraging the computational power and connectivity of the Raspberry Pi, the CaribouLite RPi HAT enables a wide range of radio-centric projects. Whether you’re interested in amateur radio, digital signal processing, or any other radio-related endeavor, this SDR platform provides the necessary tools to dive deep into the world of radio communications.

The CaribouLite Raspberry Pi radio HAT offers access to an expansive frequency spectrum. One channel is dedicated to the 30 MHz to 6 GHz range, while the other focuses on the sub-1-GHz ISM band. This broad coverage invites users to investigate and experiment with a wide array of radio frequencies, making it an invaluable asset for both learning and research. The Raspberry Pi hat is now available to purchase directly from the Crowd Supply website priced from $72.

CaribouLite HAT front view

In the spirit of collaboration and innovation, CaribouLite embraces the open-source movement. Users are provided with hardware and software that can be modified and improved upon. This approach not only benefits individual projects but also contributes to a larger community that values shared knowledge and collective advancement in radio technology. It’s important to note that CaribouLite offers versions that are designed to stay within regulatory boundaries. This ensures compliance with ETSI and FCC standards, which is essential for developers and third-party users who are creating products that must adhere to strict radio regulations.

Raspberry Pi software-defined radio (SDR) platform

For those who may be new to radio programming or even seasoned professionals, CaribouLite’s high-level API support simplifies the development process. The platform is compatible with Soapy, GNU Radio, and Python, providing a streamlined interface that allows users to fully utilize the device’s capabilities without unnecessary complexity.

The CaribouLite RPi HAT is equipped with advanced features that will delight radio aficionados. An internal TCXO clock-source guarantees precise frequency stability, a low-noise amplifier enhances signal reception, and robust transmission power increases the operational range. Additionally, PMOD expansion ports are available for those who wish to further customize and enhance the functionality of their device.

Integration with Raspbian is effortless. As soon as you power up your Raspberry Pi with the CaribouLite RPi HAT attached, it is recognized by the operating system, allowing for a smooth start to your radio projects. For advanced users, an EEPROM API is available, enabling customization of the board’s configuration to meet specific needs.

The CaribouLite Raspberry Pi radio HAT  is a remarkable example of how open-source technology can transform the capabilities of a simple Raspberry Pi into a high-performance, dual-channel SDR experience. It’s an exciting development for Raspberry Pi enthusiasts around the world.

Whether you’re a hobbyist looking to explore the airwaves or a researcher in need of a flexible radio platform, the CaribouLite RPi HAT provides the tools and features necessary to take your radio projects to the next level. With this device, the potential for discovery and innovation in the realm of radio communications is vast and waiting to be unlocked. The Raspberry Pi hat is now available to purchase directly from the Crowd Supply website priced from $72.

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Raspberry Pi Code Editor update adds support for HTML

Raspberry Pi code editor updates

The Raspberry Pi Foundation, renowned for its commitment to making programming accessible to learners of all ages, has rolled out significant updates to its Code Editor tool. These updates aim to further simplify text-based programming, particularly for young learners aged 9 and up. The most significant of these enhancements include the introduction of HTML/CSS support and an improved mobile and tablet experience.

HTML/CSS support is a major step forward in the evolution of the Code Editor. This feature enables young learners to write and run code in a web browser without the need for additional software. The HTML and CSS web development languages are now supported, allowing users to create and preview their own websites directly within the Editor interface. This seamless integration of HTML and CSS within the Code Editor tool fosters an interactive and engaging learning environment for young programmers.

The Raspberry Pi Foundation has also embedded the Code Editor in the ‘Introduction to web‘ path on the Projects site. This path contains six HTML and CSS projects specifically designed for beginners. These projects provide a hands-on approach to learning, thereby nurturing the programming skills of young learners.

Raspberry Pi Code Editor

Safety and age-appropriateness have been key considerations in the development of the Code Editor tool. The Foundation has taken proactive steps to ensure that the tool is safe and age-appropriate. For instance, certain functions such as adding links to external websites in the code have been excluded. This decision underscores the Foundation’s commitment to providing a safe and secure learning environment for young programmers.

In addition to safety measures, the Code Editor also offers several accessibility options. Users have the ability to switch between light and dark mode, catering to different lighting conditions and personal preferences. The text size can also be adjusted, ensuring that the tool is accessible to users with varying visual acuity.

The mobile and tablet experience has been significantly improved with this update. The navigation for small-screen devices is clearer, making it easier for users to navigate through the tool. All features available on desktop or laptop computers are now also accessible on mobile and tablet devices. This update greatly improves access for learners in classrooms where tablets are widely used. It also benefits learners in low- and middle-income countries where mobile phones are commonly used for digital learning.

The Raspberry Pi Foundation’s updates to the Code Editor tool are a testament to its commitment to making programming accessible and engaging for young learners. The introduction of HTML/CSS support and the improved mobile and tablet experience are significant steps forward. These updates not only enhance the learning experience, but also ensure the safety and accessibility of the tool. With these updates, the Raspberry Pi Foundation continues to demystify programming for young learners, making it an enjoyable and enriching activity.

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Raspberry Pi 5 PCIe connection unlocked via reverse engineering

Raspberry Pi 5 PCIe connection unlocked via reverse engineering

Reverse engineering is a methodical process that involves deconstructing complex systems into simpler parts to gain a comprehensive understanding of how they work. YouTuber “George Smart, M1GEO” has released an interesting video this week providing more details on his process of reverse engineering the Raspberry Pi 5 PCIe connection. The Raspberry Pi 5 compact, single-board computer was recently launched and is now available to purchase offering more power compared to its predecessor in a similar form factor.

The Raspberry Pi 5 is equipped with a PCIe connector, a vital component that enables the connection of peripherals to a computer’s motherboard. This connector is a 16-pin FPC connector, carefully designed to connect electronic devices with flexible flat cables. By expertly adjusting the kernel options, which are configurable settings for the operating system’s core, the PCIe support for the connector can be activated, thereby enhancing the device’s functionality.

Reverse engineering the Raspberry Pi 5 PCIe connection

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What is a PCIe connector?

PCIe, or Peripheral Component Interconnect Express, is a high-speed interface standard used for connecting peripheral devices to a computer’s motherboard. The PCIe connector is a part of this standard, facilitating the physical connection between the motherboard and various devices such as graphics cards, network cards, storage devices, and more.

The PCIe connector varies in size and configuration, depending on the number of lanes it supports. The lanes are the data paths in the PCIe interface; more lanes allow for greater data transfer rates. Common configurations include x1, x4, x8, and x16, where the number refers to the count of lanes. For example, a PCIe x16 connector is wider and supports higher data throughput than a PCIe x1 connector.

Physically, PCIe connectors are differentiated by their size and pin arrangement. A x16 connector is longer, to accommodate more pins, whereas a x1 connector is much shorter. Devices will fit into a slot that is the same size or larger than their connector. For instance, a PCIe x1 card can fit into a PCIe x16 slot, but not vice versa.

In practical use, PCIe connectors have enabled substantial advancements in computer performance, particularly for tasks that require high bandwidth, like gaming, video editing, and data-intensive scientific computations. The flexible nature of PCIe, supporting different sizes and configurations, has contributed significantly to its widespread adoption in modern computing systems.

Pi 5 PCIe port

Besides the PCIe connector, the Raspberry Pi 5 also features a reset signal. This is a signal used to reset a device to its initial state, essentially a reboot. This signal pulses up and then comes back down every time the device reboots, ensuring the device’s functionality remains optimal. This is a crucial aspect of the device’s functionality and is a key area of interest in the reverse engineering process.

The Raspberry Pi 5 also includes a transmit pair, clock pair, and receive pair. These are pairs of signals used in high-speed digital systems for transmitting, timing, and receiving data, respectively. The transmit pair is strategically located next to the Broadcom chip, a type of PCIe chip manufactured by Broadcom, which is part of the PCI standard. The clock pair and receive pair do not have capacitors around them on the board, which is a unique feature of the Raspberry Pi 5 that sets it apart from other devices.

Another key feature of the Raspberry Pi 5 is its connection to a 5V rail, a device that provides electrical energy. This connection is crucial for the device’s power supply, ensuring it has the necessary energy to function optimally. This is another key area of interest in the reverse engineering process, as understanding the power supply can provide valuable insights into the device’s performance.

To further understand the functionality of the Raspberry Pi 5, a breakout board was connected to the PCI Express, a high-speed serial computer expansion bus standard. By connecting six pins and ground, the PCIe works at gen one. This setup was tested with a PCIe card and a USB FireWire card, devices that provide USB and Firewire connectivity. Both of these devices were recognized by the system, indicating a successful connection and further validating the functionality of the Raspberry Pi 5.

The process of reverse engineering the Raspberry Pi 5 has provided valuable insights into its functionality. By understanding the device’s PCIe connector, reset signal, transmit pair, clock pair, and receive pair, as well as its connection to a 5V rail and the creation of a breakout board, a deeper understanding of the device’s inner workings has been achieved. This knowledge can be used to further advance the projects and applications that the Pi 5 can be used for and improve its performance and capabilities.

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How to reduce your Raspberry Pi 5 power consumption by 140x

How to reduce your Raspberry Pi 5 power consumption

The Raspberry Pi 5, a mini PC that is now available for purchase, has been praised for its enhanced capabilities and increased power when compared to the previous Raspberry Pi 4. However this increased processing power also draws high power consumption, especially in Power Off mode. This high power consumption is not a feature unique to the Raspberry Pi 5, but is also a characteristic of its predecessor, the Raspberry Pi 4. Both these models, by default, leave the System on a Chip (SoC) powered up in a shutdown state, leading to power consumption of 1.2-1.6W, even when no other peripherals are plugged in other than the power source.

The default setting of the Raspberry Pi 5 is a significant contributor to its high power consumption. This is due to the fact that some Hardware Attached on Top (HATs) experience issues if the 3v3 power rail is off, but the 5v is still active. As such, the Raspberry Pi 5 ships with the setting POWER_OFF_ON_HALT=0, causing it to continuously consume power.

Reduce Raspberry Pi 5 power consumption

Fortunately, a solution has been developed to mitigate this issue. Jeff Geerling, a well-known figure in the Raspberry Pi community, has developed a method to reduce the Raspberry Pi’s power consumption by up to 140 times while in Power Off mode. This solution involves editing the Electrically Erasable Programmable Read-Only Memory (EEPROM) configuration and adjusting the following settings: BOOT_UART=1, WAKE_ON_GPIO=0, POWER_OFF_ON_HALT=1.

The process of editing the EEPROM configuration is straightforward. After saving the configuration and rebooting, the power consumption should significantly decrease from 1-2W to 0.01W or less when shut down. This is a remarkable reduction, making the Raspberry Pi 5 much more energy-efficient in Power Off mode.

Reduce Raspberry Pi 5 power consumption

Importantly, the functionality of the Raspberry Pi 5 is not compromised by implementing this solution. The Raspberry Pi 5 can still boot with the POWER_OFF_ON_HALT setting, the power button still operates as expected, and the red LED remains illuminated when the device is shut down. Moreover, the Real-Time Clock (RTC) continues to keep time, indicating that watchdog-related functions should also continue to operate normally.

While the Raspberry Pi 5 does have a high power consumption in its default Power Off mode, this issue can be effectively addressed. By editing the EEPROM configuration, users can significantly reduce the device’s power consumption without compromising its functionalities. This solution represents a significant stride towards making the Raspberry Pi 5 more energy-efficient and environmentally friendly.

Image Source :  Jeff Geerling

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Raspberry Pi receives investment from Arm

Raspberry Pi receives investment from Arm

Arm Holdings plc, a global leader in semiconductor and software design, has recently made a strategic investment in Raspberry Pi Ltd, acquiring a minority stake in the company. This move signifies a continuation and strengthening of a successful long-term partnership between the two companies, which began in 2008. The collaboration between Arm and Raspberry Pi primarily aims to deliver critical solutions for the Internet of Things (IoT) developer community.

The demand for edge computing is accelerating due to the proliferation of more demanding IoT and AI applications. Edge computing refers to the practice of processing data near the edge of the network, where the data is being generated, instead of in a centralized data-processing warehouse. This move is driven by the need for faster processing speeds, reduced bandwidth usage, and lower latency.

Raspberry Pi Arm investment

Raspberry Pi, a UK-based technology company, is a significant player in this space. Its solutions are providing low-cost, high-performance computing to people and businesses worldwide. The Raspberry Pi devices, which are small, single-board computers, have gained immense popularity for their affordability and versatility. These devices have found a wide range of applications, from personal projects and educational tools to industrial IoT.

“Arm technology has always been central to the platforms we create, and this investment is an important milestone in our longstanding partnership,” said Eben Upton, CEO, Raspberry Pi. “Using Arm technology as the foundation of our current and future products offers us access to the compute performance, energy efficiency and extensive software ecosystem we need, as we continue to remove barriers to entry for everyone, from students and enthusiasts, to professional developers deploying commercial IoT systems at scale.”

The partnership between Arm and Raspberry Pi has resulted in the release of many popular Arm-based Raspberry Pi products for students, enthusiasts, and commercial developers. The most recent flagship product, the Raspberry Pi 5, became available at the end of October. This device, like its predecessors, is expected to further the companies’ shared vision of making computing accessible for all by lowering barriers to innovation.

“Arm and Raspberry Pi share a vision to make computing accessible for all, by lowering barriers to innovation so that anyone, anywhere can learn, experience and create new IoT solutions,” said Paul Williamson, SVP and GM, Internet of Things Line of Business, Arm. “With the rapid growth of edge and endpoint AI applications, platforms like those from Raspberry Pi, built on Arm, are critical to driving the adoption of high-performance IoT devices globally by enabling developers to innovate faster and more easily. This strategic investment is further proof of our continued commitment to the developer community, and to our partnership with Raspberry Pi.”

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The platforms from Raspberry Pi, built on Arm technology, are critical to driving the adoption of high-performance IoT devices globally. Arm technology is central to the platforms created by Raspberry Pi, providing access to compute performance, energy efficiency, and an extensive software ecosystem. This ecosystem includes a wide range of software tools, libraries, and services that developers can use to build and deploy applications.

The strategic investment by Arm is a testament to their continued commitment to the developer community and their partnership with Raspberry Pi. This move not only strengthens their relationship but also reinforces Arm’s dedication to fostering innovation within the global computing community.

Raspberry Pi, with the backing of Arm, aims to continue removing barriers to entry for everyone, from students and enthusiasts to professional developers deploying commercial IoT systems at scale. Through their hardware and software solutions, they are making high-performance computing accessible to a broader audience and enabling the development of innovative applications in the IoT space.

Arm’s investment in Raspberry Pi signifies a significant step in the advancement of accessible, high-performance computing. By combining Arm’s cutting-edge technology with Raspberry Pi’s commitment to affordability and accessibility, the partnership is poised to drive innovation and growth in the IoT developer community.

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How to run AI models on a Raspberry Pi and single board computers (SBC)

running AI models on single board computers SBC

If you are looking for a project to keep you busy this weekend you might be interested to know that it is possible to run artificial intelligence in the form of large language models (LLM) on small single board computers (SBC) such as the Raspberry Pi and others. With the launch of the new Raspberry Pi 5 this month its now possible to carry out more power intensive tasks to its increased performance.

Although before you start it’s worth remembering that running AI models, particularly large language models (LLMs), on a Raspberry Pi or other SBCs presents an interesting blend of challenges and opportunities. While you trade off computational power and convenience, you gain in terms of cost-effectiveness, privacy, and hands-on learning. It’s a field ripe for exploration, and for those willing to navigate its limitations, the potential for innovation is significant.

One of the best ways of accessing ChatGPT from your Raspberry Pi setting up a connection to the OpenAI API, building programs using Python, JavaScript and other programming languages to connect to ChatGPT remotely. Although if you are looking for a a more locally installed more secure version which runs AI directly on your mini PC you will need to select a lightweight LLM that is capable of running and answering your queries more effectively.

Running AI models on a Raspberry Pi

Watch the video below to learn more about how this can be accomplished thanks to Data Slayer if you are interested in learning more about how to utilize the power of your mini PC I deftly recommend you check out his other videos.

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Before diving in, it’s important to outline the challenges. Running a full-scale LLM on a Raspberry Pi is not as straightforward as running a simple Python script. These challenges are primarily:

  • Limited Hardware Resources: Raspberry Pi offers less computational power compared to typical cloud-based setups.
  • Memory Constraints: RAM can be a bottleneck.
  • Power Consumption: LLMs are known to be energy-hungry.

Benefits of running LLM is on single board computers

Firstly, there’s the compelling advantage of affordability. Deploying AI models on cloud services can accumulate costs over time, especially if you require significant computational power or need to handle large data sets. Running the model on a Raspberry Pi, on the other hand, is substantially cheaper in the long run. Secondly, you gain the benefit of privacy. Your data never leaves your local network, a perk that’s especially valuable for sensitive or proprietary information. Last but not least, there’s the educational aspect. The hands-on experience of setting up the hardware, installing the software, and troubleshooting issues as they arise can be a tremendous learning opportunity.

Drawbacks due to the lack of computational power

However, these benefits come with distinct drawbacks. One major issue is the limited hardware resources of Raspberry Pis and similar SBCs. These devices are not designed to be powerhouses; they lack the robust computational capabilities of a dedicated server or even a high-end personal computer. This limitation is particularly pronounced when it comes to running Large Language Models (LLMs), which are notorious for their appetite for computational resources. Memory is another concern; Raspberry Pis often come with a limited amount of RAM, making it challenging to run data-intensive models. Furthermore, power consumption can escalate quickly, negating some of the cost advantages initially gained by avoiding cloud services.

Setting up your mini PC

Despite these challenges, there have been advancements that make it possible to run LLMs on small computers like Raspberry Pi. One notable example is the work of Georgie Gregov, who ported the Llama model, a collection of private LLMs shared by Facebook, to C++. This reduced the size of the model significantly, making it possible to run on tiny devices like Raspberry Pi.

Running an LLM on a Raspberry Pi is a multi-step process. First, the Ubuntu server is loaded onto the Raspberry Pi. An external drive is then mounted to the Pi, and the model is downloaded to the drive. The next step involves cloning a git repo, compiling it, and moving the model into the repo file. Finally, the LLM is run on the Raspberry Pi. While the process might be a bit slow, it can handle concrete questions well.

It’s important to note that LLMs are still largely proprietary and closed-source. While Facebook has released an open-source version of its Llama model, many others are not publicly available. This can limit the accessibility and widespread use of these models. One notable example is the work of Georgie Gregov, who ported the Llama model, a collection of private LLMs shared by Facebook, to C++. This reduced the size of the model significantly, making it possible to run on tiny devices like Raspberry Pi.

Running AI models on compact platforms like Raspberry Pi and other single-board computers (SBCs) presents a fascinating mix of advantages and limitations. On the positive side, deploying AI locally on such devices is cost-effective in the long run, eliminating the recurring expenses associated with cloud-based services. There’s also an increased level of data privacy, as all computations are carried out within your own local network. Additionally, the hands-on experience of setting up and running these models offers valuable educational insights, especially for those interested in the nitty-gritty of both hardware and software.

However, these benefits come with their own set of challenges. The most glaring issue is the constraint on hardware resources, particularly when attempting to run Large Language Models (LLMs). These models are computational and memory-intensive, and a Raspberry Pi’s limited hardware isn’t built to handle such heavy loads. Power consumption can also become an issue, potentially offsetting some of the initial cost benefits.

In a nutshell, while running AI models on Raspberry Pi and similar platforms is an enticing proposition that offers affordability, privacy, and educational value, it’s not without its hurdles. The limitations in computational power, memory, and energy efficiency can be significant, especially when dealing with larger, more complex models like LLMs. Nevertheless, for those willing to tackle these challenges, the field holds considerable potential for innovation and hands-on learning.

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MagPi Raspberry Pi 5 special launch edition magazine

MagPi Raspberry Pi 5 special magazine 135

Hot on the heels of the official launch and availability of the new Raspberry Pi 5 mini PC this week which is now available to purchase after being officially unveiled last month. The Raspberry Pi team has also released a special launch edition of the fantastic MagPi magazine. providing you with everything you need to get started using the more powerful Pi 5 mini PC and its new features, hardware and enhancements.

The MagPi magazine issue #135, the official Raspberry Pi magazine, has dedicated its special edition to this noteworthy launch. It not only provides an in-depth look at the  Pi 5 but also features 50 Raspberry Pi project ideas, innovative community projects, and tutorials on using Raspberry Pi and Ubuntu.

The Raspberry Pi 5 is a game-changer in the Raspberry Pi line-up, boasting 2–3× the speed of the previous generation. This is primarily due to the Broadcom BCM2712 quad-core Arm Cortex A76 processor @ 2.4GHz, making it up to three times faster than its predecessor. With RAM variants up to 8GB, Pi 5 promises the fastest, smoothest Raspberry Pi experience yet.

Raspberry Pi 5

Other articles we have written that you may find of interest on the new mini PC :

Another first for the Pi 5 is the use of the RP1 I/O controller, a package containing silicon designed in-house at Raspberry Pi. This move towards in-house silicon design is a significant milestone for the Raspberry Pi team and is likely to contribute to the enhanced performance of the device.

The Raspberry Pi 5 has also introduced PCI express, a feature that allows you to connect an M.2 SSD to your Raspberry Pi. This addition ensures speedy data transfer and super-fast boot, enhancing the overall user experience. The latest release of Raspberry Pi OS is designed to maximize these new features, delivering an excellent desktop performance suitable for work, leisure, enterprise, and more.

The Pi 5 is not just about speed; it also brings a host of new features to the table. The device supports dual 4Kp60 HDMI® display output and has a 4Kp60 HEVC decoder. It also includes dual-band 802.11ac Wi-Fi®, Bluetooth 5.0 / Bluetooth Low Energy (BLE), and a high-speed microSD card interface with SDR104 mode support. The device also features 2 × USB 3.0 ports, supporting simultaneous 5Gbps operation, and 2 × USB 2.0 ports.

The Raspberry Pi 5 also has interchangeable camera and DSI display connectors, allowing users to have one of each or two of the same, providing more flexibility in configuration. The device also supports Gigabit Ethernet, with PoE+ support (requires separate PoE+ HAT, coming soon). It also includes 2 × 4-lane MIPI camera/display transceivers and a PCIe 2.0 x1 interface for fast peripherals. The device maintains the Raspberry Pi standard 40-pin GPIO header and introduces a real-time clock and a power button.

Priced at $60 for the 4GB variant, and $80 for the 8GB version (plus local taxes), the Pi 5 mini PCrepresents a significant upgrade in virtually every aspect of the platform, delivering a no-compromises user experience.

Raspberry Pi specifications

  • 2.4GHz quad-core 64-bit Arm Cortex-A76 CPU
  • VideoCore VII GPU, supporting OpenGL ES 3.1, Vulkan 1.2
  • Dual 4Kp60 HDMI® display output
  • 4Kp60 HEVC decoder
  • Dual-band 802.11ac Wi-Fi®
  • Bluetooth 5.0 / Bluetooth Low Energy (BLE)
  • High-speed microSD card interface with SDR104 mode support
  • 2 × USB 3.0 ports, supporting simultaneous 5Gbps operation
  • 2 × USB 2.0 ports
  • Gigabit Ethernet, with PoE+ support (requires separate PoE+ HAT, coming soon)
  • 2 × 4-lane MIPI camera/display transceivers
  • PCIe 2.0 x1 interface for fast peripherals
  • Raspberry Pi standard 40-pin GPIO header
  • Real-time clock
  • Power button

The MagPi magazine issue #135 not only covers these impressive features of the Raspberry Pi 5 but also provides readers with a wealth of project ideas and tutorials. Whether you are a seasoned Raspberry Pi user or a newcomer to the community, this special edition is a treasure trove of information and inspiration. It showcases the potential of the Raspberry Pi 5 and encourages users to push the boundaries of what is possible with this powerful, versatile device.

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Raspberry Pi Industrial Multi-iO HAT designed for automation

Raspberry Pi Industrial Multi-iO HAT designed for automation

Anyone creating autonomous systems using the Raspberry Pi range of mini PCs might be interested in the new Multi-iO HAT  specifically designed for Raspberry Pi automation. Compatible with all Raspberry Pi versions, from Raspberry Pi Zero to Raspberry Pi 5. This compatibility is achieved through the use of the I2C port, demonstrating the device’s adaptability and interoperability.

The Multi-iO HAT’s compatibility with all Raspberry Pi versions ensures that it can be integrated seamlessly into a variety of setups, offering a high degree of flexibility for users. Exclusive early bird pledges are now available for the interesting project from roughly $70 or £58 (depending on current exchange rates).

Raspberry Pi HAT

In terms of functionality, the Multi-iO HAT is equipped with multiple digital and analog inputs and outputs. This includes two opto-isolated or four common ground digital inputs, two 0-10V and two 4-20mA analog inputs and outputs. The device also features two 3-wire RTD ports with 24 bit delta-sigma A/D converters, enabling accurate RTD measurement. This multitude of inputs and outputs allows the Multi-iO HAT to handle a wide range of tasks, making it a versatile tool in the field of automation.

Moreover, the HAT comes with two 5A/24V relays with normal-open contacts and status LEDs. These relays enhance the device’s capabilities, allowing it to control various electrical circuits. The device also includes a H-Bridge PWM micro-motor driver and two servo control ports, further augmenting its function in automation processes.

Industrial Automation

The Multi-iO HAT stands out with its expandability to eight layers. This feature allows users to increase the IO capabilities of the device, making it suitable for more complex tasks. Up to eight Multi-iO HATs can be stacked on top of each Raspberry Pi, demonstrating the device’s scalability.

If the Multi-iO HAT crowd funding campaign successfully raises its required pledge goal and the project completion progresses smoothly, worldwide shipping is expected to take place sometime around January 2024. Other articles we have written that you may find of interest on the subject of Raspberry Pi 5 the latest mini PC to be added to the range.

Specifications and features

  • Uses only I2C port, works with all Raspberry Pi versions from Zero to 5
  • Wide range 10-30V power supply provides also 5V/3A to Raspberry Pi
  • Two opto-isolated or four common ground digital inputs
  • Two 3-wire RTD ports with 24 bit delta-sigma A/D converters
  • Two 0-10V Analog Inputs
  • Two 4-20mA Analog Inputs
  • Two 0-10V Analog Outputs
  • Two 4-20mA Analog Outputs
  • Two 5A/24V relays with normal-open contacts and status LEDs
  • Two communication ports: RS485/Modbus and RS232
  • H-Bridge PWM micro-motor driver
  • Two servo control ports
  • Nine Status LEDs (six general purpose)
  • On-board push-button
  • Real Time Clock with battery backup (battery not included)
  • Hardware Watchdog
  • Pluggable Connectors
  • Stand-alone operation (No Raspberry Pi) using RS485/MODBUS
  • Eight layer stackable for IO expansion
  • Command Line Driver, Python Library, Node-Red nodes

Digital and analog inputs and outputs

The device is powered by a 10-30V power supply, which also provides 5V/3A to the Raspberry Pi. This wide range power supply ensures that the MULTI-IO HAT can function efficiently in various settings. It also includes nine status LEDs, an on-board push-button, a Real Time Clock with battery backup, and a hardware watchdog. These features enhance the user experience, providing real-time status updates and ensuring the device’s reliability.

Communication is a crucial aspect of automation, and the Multi-iO HAT does not disappoint in this regard. It comes with two communication ports, RS485/Modbus and RS232. These ports facilitate communication between the device and other components in an automation system. Moreover, the MULTI-IO HAT can operate stand-alone, without a Raspberry Pi, using RS485/MODBUS.

The Raspberry Pi automation HAT also comes with a Command Line Driver, Python Library, and Node-Red nodes. These features make the device more accessible and easier to use, allowing users to control and manipulate the device using various programming languages.

The HAT offers users a robust and versatile device that is essential in modern industrial and home automation. Its compatibility with all Raspberry Pi versions, multiple digital and analog inputs and outputs, RTD measurement and relay capabilities, and expandability to eight layers make it a standout choice in the field of automation. Whether used with a Raspberry Pi or in stand-alone mode, the Raspberry Pi automation HAT offers a range of solutions for autonomous tasks, making it a valuable tool for professionals and hobbyists alike.

For a complete list of all available pledge options, stretch goals, extra media and technical attributes for the Raspberry Pi automation system, jump over to the official Multi-iO HAT crowd funding campaign page by navigating to the link below.

Source : Kickstarter

Disclaimer: Participating in Kickstarter campaigns involves inherent risks. While many projects successfully meet their goals, others may fail to deliver due to numerous challenges. Always conduct thorough research and exercise caution when pledging your hard-earned money.

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