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    Autonomous Driving Data Storage Solution

    Fuel autonomous driving with OceanStor Pacific series storage.

The High Data Processing Needs of Autonomous Driving

  • Massive Amounts of Road Data Generated

    • Upgraded autonomous driving models generate massive amounts of road data and at L4 — considered to be fully autonomous — there are three to five times more test data compared to L3: hundreds of TB need to be imported and stored every day.
    • Of all collected data, approximately 15% needs to be pre-processed, with PBs of data that needs to be archived for over a decade.

  • One Service Set Involves Multiple Protocols

    • Test data transmission, import, preprocessing, training, simulation, and result analysis require different protocols, including object storage, Network Attached Storage (NAS), and Hadoop Distributed File System (HDFS).
    • Diverse Data is radically siloed, so much so that copying data takes longer than processing and analyzing it, dragging down efficiency.

  • Complex Service Models and High Performance Needs

    • There are various types of road test data sensors and complex service Input/Output (I/O) models. Extremely high performing Information Technology (IT) infrastructure is required for vehicle model algorithm training and function simulation.

How You Can Benefit from Huawei's Solution

  • Ultra-High Density

    • A single OceanStor Pacific 9550 chassis with two nodes accommodates road data collected by 500 vehicles.

  • Multi-Protocol Interworking

    • One copy of metadata and one copy of data can be accessed by multiple services, breaking down silos.
    • As results a result, efficiency is improved by 25%, lowering Total Cost of Ownership (TCO) by 20%.

  • Superior Performance

    • A 5U chassis delivers bandwidth of 160 Gbit/s and 2 million IOPS.
    • Performance density is 30% higher than the industry average.

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