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Small Form Factor Module

Aetina provides a variety of small form factor (SFF) modules with compact architecture, targeting applications that usually require high performance computing in limited space. SFF modules include M.2 Module, Mini PCIe(mPCle) Module, Mobile PCIe Module(MXM), expansion kit, and one-stop thermal service.

M.2 Module and Mini PCIe Module are AI accelerator Modules for AI applications, delivering unprecedented AI performance for edge devices. They both can be quickly plugged into existing edge devices to execute in real-time. With low-power deep neural network inference, M.2 Module and Mini PCIe Module are suitable for a broad range of market segments. Metion to Mobile PCI Express Module (MXM), it features compact commercial off-the-shelf (COTS) solution. It leverages parallel processing performance, delivering unmatched power efficiency. With high-level compute capability, MXM is ideal for embedded system that is demanding performance, size, weight and power (SWaP) constrained.

As the dimensions of small form factor modules are inconsistent in the market, it’s inconvenient for users to customize heat dissipation design to avoid the occurrence of high temperature failure especially when developing high computing performance applications in smart medical, factory automation, and so on. To improve the situation, Aetina decide to roll out one-stop thermal service, including standard heat spreaders, optional semi sink, and customized cooler.



• Increase the area of dissipation for each IC component
• Handle temperature overheat issue not merely for GPU but memory as well
• High-watt heat spreader is made of copper, and low-watt one is aluminum
• Easy assembly
• Save extra jiq cost

In the early stages of AI deep learning project development, developers spend lots of cost and time building a test system to confirm performance specifications and related peripheral devices. To solve the problem, Aetina expansion kits provide onboard high-performance computing modules with various applications of deep learning for computer vision.


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