구글 머신러닝 Coral Mini PCIe 엑셀레이터 모듈
(Coral Mini PCIe Accelerator)
개요
- 본 제품은 구글 머신러닝 Coral Mini PCIe 엑셀레이터 모듈입니다.
- Google의 Edge TPU 코프로세서를, 머신 러닝기능을 추가하고자 하는 임베디드 시스템에 사용이 가능한 제품입니다.
- Coral Mini PCIe 엑셀레이터는 표준 Mini PCIe 슬롯에 맞게 디자인되었습니다.
- Edge TPU는 구글이 제공하는 머신 러링 ASIC입니다.
특징
- Performs high-speed ML inferencing: The on-board Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 400 FPS, in a power efficient manner.
- Works with Debian Linux: Integrates with any Debian-based Linux system with a compatible card module slot.
- Supports TensorFlow Lite: No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU.
- Supports AutoML Vision Edge: Easily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge.
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Physical specifications Dimensions 30.00 x 26.80 x 2.55 mm Weight 3.6 g Host interface Hardware interface Half-Mini PCIe card Serial interface PCIe Gen2 x1 Operating voltage DC supply 3.3V +/- 10 % Environmental reliability Temperature -40 ~ 85° C (storage)
-20 ~ 70° C (operating)Relative humidity 0 ~ 100% (non-condensing) Mechanical reliability Op-shock 100 G, 11ms (persistent)
1000 G, 0.5 ms (stress)
1000 G, 1.0 ms (stress)Op-vibe (random) 0.5 Grms, 5 - 500 Hz (persistent)
3 Grms, 5 - 800 Hz (stress)Op-vibe (sinusoidal) 0.5 Grms, 5 - 500 Hz (persistent)
3 Grms, 5 - 800 Hz (stress)