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SOTA: MLPerf inference benchmark v0.5 results snapshot (open, Research, Development, and Other) for collaborative validation

result:sota-mlperf-inference-results-v0.5-open-rdo (v1.0.0)
License: https://github.com/mlperf/policies/blob/master/TERMS%20OF%20USE.md
Creation date: 2019-11-07
Source: mlperf.org/inference-overview/#overview
cID: 4cd2850867df4241:8e45edab745c8867
Push data to this graph: docs , graph meta description
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Benchmark results (performance): P_*_SS - Single Stream in milliseconds, P_*_MS - MultiStream in no. streams, P_*_S - Server in QPS, P_*_O - Offline in inputs/second.
Benchmark results (accuracy): A_IC* - Top-1, A_OD* - mAP, A_NMT* - BLEU.
cK components: packages, software detection plugins.
Image Classification: IC1 - ImageNet, MobileNet-v1, IC2 - ImageNet, ResNet-50 v1.5.
Object detection: OD1 - COCO, SSD w/ MobileNet-v1, OD2 - COCO 1200x1200, SSD w/ ResNet-34.
Translation: NMT - WMT E-G, NMT.
Form Factor: FF_M - Mobile/Handheld, FF_D - Desktop/Workstation, FF_S - Server, FF_E - Edge/Embedded.
These are not official results but a snapshot to collaboratively reproduce results and add portable workflows!
MLPerf name and logo are trademarks. See www.mlperf.org for more information.

Reproduced paper: MLPerf Inference Benchmark
Related reusable solutions:   1     2     3     4     5     6     7  




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