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    Autonomous Driving Data Storage Solution

    Fuel autonomous driving with OceanStor Pacific series storage.

Overview

  • Overview
  • Benefits
  • Architecture
  • Products

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.

Benefits

Multi-layer Ecosystem

Ultra-High Density

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

Converged Forwarding

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%.

optimize business experience

Superior Performance

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

Architecture

automotive storage architecture en
Huawei

Products

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