Huawei ATLAS 300 HH/HL 02312JPM
 | Outdated Product A special computing accelerator based on the innovative Da Vinci architecture, focused on use in high-performance systems using machine learning algorithms (Machine Learning). Designed as a standard expansion card with a fast PCI-E Gen4 x16 interface. The device is based on the innovative Ascend 310 processor, designed specifically for solving problems of machine learning and artificial intelligence. The Huawei ATLAS 300 HH/HL 02312JPM Computing Accelerator provides the highest performance (up to 64 TOPS in INT8 calculations). It is focused on the implementation of the functions of analyzing multi-channel HD-video (up to 64 channels simultaneously) in real time. Provides low latency due to high performance. High bandwidth and large memory capacity allow this accelerator to be used in profe...ssional face recognition systems. Demonstrates impressive energy efficiency — the power consumption in the process of analyzing a 64-channel video signal does not exceed 67 watts. Recommended for use in data centers and enterprise analysis systems. |
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Huawei ATLAS 300 HH/HL 02312JPM 2021 | |||
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A special computing accelerator based on the innovative Da Vinci architecture, focused on use in high-performance systems using machine learning algorithms (Machine Learning). Designed as a standard expansion card with a fast PCI-E Gen4 x16 interface. The device is based on the innovative Ascend 310 processor, designed specifically for solving problems of machine learning and artificial intelligence.
The Huawei ATLAS 300 HH/HL 02312JPM Computing Accelerator provides the highest performance (up to 64 TOPS in INT8 calculations). It is focused on the implementation of the functions of analyzing multi-channel HD-video (up to 64 channels simultaneously) in real time. Provides low latency due to high performance. High bandwidth and large memory capacity allow this accelerator to be used in professional face recognition systems. Demonstrates impressive energy efficiency — the power consumption in the process of analyzing a 64-channel video signal does not exceed 67 watts. Recommended for use in data centers and enterprise analysis systems.
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