Merge pull request #22 from mlbench/Fix-mlbench-vs-mlperf

Mark post as published and add date

Author: Edoardo Holzl

_posts/mlbench-vs-mlperf.md _posts/2020-09-17-mlbench-vs-mlperf.md_posts/mlbench-vs-mlperf.md renamed to _posts/2020-09-17-mlbench-vs-mlperf.md

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 layout: post
 title: Comparison of MLBench and MLPerf
 author: m_milenkoski
+published: true
+tags: [mlperf, introduction]
+excerpt_separator: <!--more-->
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 MLPerf is a broad benchmark suite for measuring the performance of machine learning (ML) software frameworks, ML hardware platforms and ML cloud platforms. 
 
 In this post, we will highlight the main differences between MLBench and MLPerf. 
 
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 ## Key Advantages of MLBench
 
 - Reference implementations for distributed execution instead of only single-node execution as in MLPerf