NVIDIA Jetson Nano Lot boards

The developer kit is powered by micro-USB. It also supports NVIDIA JetPack which includes a board support pack (BSP), Linux OS and NVIDIACUDA(r), cuDNN and TensorRTTM software libraries for deep learning and computer vision. It is also available as an easy-to flash SD card image which makes it simple to get started. The best thing about the JetPack SDK is that it can be used across all NVIDIA Jetson products. This allows full compatibility with NVIDIA's AI platform, which is the world's most trusted for training and deploying AI programs. This reduces the complexity and work required by developers. Buy NVIDIA Tesla m10 Quad GPU module online in India, Shop all kind of Refurbished IT spare online at Sureworks.store




NVIDIA Jetson Nano Lot boards


Advantages

The biggest advantage is the fact that it's an AI computing platform with GPU-accelerated parallel processing. Jetson Nano features a 128 CUDA Core GPU based on Maxwell architecture. Nvidia also has an open-source project called Jetson Inference. It runs on all Jetson platforms including the Nano. Jetson Interference shows various machine learning techniques, such as object recognition or object detection. This makes the Nano a great starting point for developers who want to create real-world machine learining projects.

The disadvantages 

Although the hardware is impressive, software support needs to be better. Cost is another factor that deters people from buying it. It is priced at $99 and much more expensive than other competitors such as Raspberry Pi.


NVIDIA Jetson Nano projects

 The Jetson Nano is used to develop scores of small, low-power Artificial Intelligence systems (AI). It's also very popular for embedded IoT applications such as entry-level Network Video Recorders, home robots and intelligent gateways that have full analytics capabilities.

ODROID board

ODROIDrefers to a series of single-board computers and tablet computers created by the South Korean company, Hardkernel Co, Ltd. The term ODROID is a portmanteau for open + Android. However, the hardware is not open as some parts of its design are kept by the company. Several ODROID systems can run regular Linux distributions as well as Android


The ODROID boards look very similar to Raspberry Pi. In many cases, they perform better. These boards typically come with a faster CPU, more RAM, and a higher price. The XU models have an Exynos SoC, while the C models have an Amlogic system-on-a-chip (SoC). Both models have an ARM CPU as well as an on-chip GPU. The CPU architectures are ARMv7 and ARMv8. However, the boards memory ranges between 1 GB RAM and 2 GB RAM. The majority of boards include three to five USB 2.0 or 3.0 slots, HDMI output and a 3,5 mm jack. A lot of the general-purpose input/output pins (GPIO) offer a lower output. The latest models include a Gigabit Ethernet (8P8C), port, and eMMC socket. SD cards, like the Raspberry Pis are used to store operating system and program memories in the SDHC and MicroSDHC sizes.

Advantages

 ODROID boards are generally faster than Raspberry Pis, particularly up to Raspberry Pi 3. Another advantage is the ODROID C2's large heat sink. The ODROID C2 board layout is nearly identical to that of the Pi B+/2/3. The largest components, such as LAN, USB and HDMI, OTG and the mounting holes, are identically placed. This allows anyone with the right mounts/cases to mount a Pi to work easily with an ODROID–C2 (in most cases anyway).

The disadvantages 

ODROID boards over Raspberry Pi are that they are more expensive. Raspberry Pis are more affordable because they have in-built Bluetooth or Wifi. ODROID boards don't have the same software quality and community support as Raspberry Pis. It should be noted that Raspberry Pi 4 has made it more difficult for people to choose ODROID boards.


ONDROID projects ODROID boards can be used for many fun projects, including building digital photo frames or environmental sensors for gaming machines.


Advantages: 

The biggest advantage is the fact that it's an AI computing platform with GPU-accelerated parallel processing. Jetson Nano features a 128 CUDA Core GPU based on Maxwell architecture. Nvidia also has an open-source project called Jetson Inference. It runs on all Jetson platforms including the Nano. Jetson Interference shows various machine learning techniques, such as object recognition or object detection. This makes the Nano a great starting point for developers who want to create real-world machine learning projects.


The disadvantages

Although the hardware is impressive, software support needs to be better. Cost is another factor that deters people from buying it. It is priced at $99 and much more expensive than other competitors such as Raspberry Pi.


NVIDIA Jetson Nano projects 

 The Jetson Nano is used to develop scores of small, low-power Artificial Intelligence systems (AI). It's also very popular for embedded IoT applications such as entry-level Network Video Recorders, home robots and intelligent gateways that have full analytics capabilities.


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