The launch of the Raspberry Pi 4 has brought attention to the single board computer market as a whole. The Pi 4 breathed new life and brought a lot of new participants to the market, and with its low barrier for entry and use for ML tasks.
With the initial launch of the Raspberry Pi, there were a host of other alternatives that came up with it. For those enthusiasts not interested in buying a Pi, the single-board computer market accommodated and created various new products.
However, which one of them is most suited for AI and ML tasks? In this article, we will be looking at the Raspberry Pi 4 alongside the Banana Pi and Rock Pi. These popular alternatives are usually also used for similar applications, so a side by side comparison will bring the winner out on top.
The criteria used to judge the computers will be as follows:
Core count and speed: The core speed of the processor on the board is extremely important, as this governs how fast programs will be able to run. The higher the speed is, the more effective it will be to run a program on the processor.
The core count is useful for multi-threaded workloads and similar applications, with a higher core count denoting the amount of power a processor can output on a whole. This is useful for parallelism.
GPU acceleration capabilities: Even though no one will use a Pi for training an algorithm, the presence of an on-board GPU will cut down on the time required for inference. A wide variety of machine learning workloads feature GPU acceleration for parallelism and resource management.
Memory Speed: The speed of the on-die RAM set is important to the roundup as well, as this determines the speed at which the model can be accessed from the database. Moreover, the RAM cannot be changed or swapped out, as it is soldered on the board.
Raspberry Pi 4 Model B
This is the latest iteration in the original series of single-board computers, and has enough computing power to be a low-powered desktop replacement for low-end users. The star of the show is the Broadcom CPU, based on the A72 chipset. The chip has 4 cores, along with a clock speed of 1.5GHz.
The GPU that is available on the Pi is the Broadcom VideoCore VI, and is said to offer a 50% increase in performance over previous models. It is mainly used for high-speed HEVC encode/decode.
The RAM on the chip is also fairly fast, with the option for 4GB of LPDDR4 SDRAM being the most suited for this use case. Official benchmarks show access speeds upwards of 4100/4400 MBps for read and write respectively.
Rock Pi 4B v1.3
The Rock Pi is a single board computer with slightly higher specs than the Raspberry Pi, and comes with the added benefit of being able to run Android. at its heart, the Rock Pi runs on an ARM-based processor known as the Rockchip.
The Rockchip features a dual CPU, with the primary being a quad-core A72 chipset. In addition to this, there is a secondary CPU in the form of the A52 chipset. The clock speeds for these are 1.8GHz and 1.4GHz respectively.
The GPU on the Rock Pi is also high-powered, with the Mali T860MP4 GPU being more than enough to handle 4K 30FPS playback. Moreover, the Rock Pi is also slated for a neural processing unit acceleration in its next iteration. The RAM is of a LPDDR4 variant that runs at 3200 MBps.
Banana Pi BPi-M3
Banana Pi provides a whole lineup of single-board computers for various use-cases. However, we will be looking at their most powerful product, the BPi-M3.
The underdog in this lineup, the BPi-M3 runs on an octa-core configuration on an ARM-A7 core. The eight cores are sure to give it an edge in multi-threaded workloads. The clock speed of 1.8GHz will also give it an advantage over lower-clocked systems.
The GPU on board is fairly low-powered, and will not be suitable for acceleration in any form. The RAM is also of the LPDDR3 variant, and tops out at 2GB. This is not ideal, as the DDR4 variant offers higher speeds for RAM access.
For AI and ML tasks in a low-powered environment, the Rock Pi comes out on top. With a capable CPU, GPU and upcoming NPU, this single-board computer stands above the rest in computing power. However, it is to be noted that the Raspberry Pi has better documentation and a more robust community for bug-testing.
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