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MLPerf™ Inference v2.1 with NVIDIA GPU-Based Benchmarks on Dell PowerEdge Servers
Introduction What is new in MLPerf Inference v2.1?
Summary
Growth of MLPerf Inference as a benchmark Dell results Notable results Highlighting performance scores System performance details PowerEdge server, GPU, and Software specifications Performance improvements Conclusion and Key Takeaways Acknowledgment References

Summary

Home > AI Solutions > Artificial Intelligence > White Papers > MLPerf™ Inference v2.1 with NVIDIA GPU-Based Benchmarks on Dell PowerEdge Servers > Summary

Summary

  • New features of MLPerf Inference v2.1include:

    • A new object detection benchmark: RetinaNet using a ResNeXT50 backbone. This reference model is more accurate than its predecessor and trains on the Open Images dataset, which is larger and more realistic than COCO.
    • Inference over the network scenario: A remote system injects queries over the network into the SUT. This scenario more faithfully models real data center systems compared to starting with queries in host DRAM.