Traditional　reasoning　tools　for　the　Semantic　Web　cannot　cope　with　Web　scale　data.　One　major　direction　to　improve　performance　is　parallelization.　This　article　surveys　existing　studies,　basic　ideas　and　mechanisms　for　parallel　reasoning,　and　introduces　three　major　parallel　applications　on　the　Semantic　Web:　LarKC,　MaRVIN,　and　Reasoning-Hadoop.　Furthermore,　this　paper　lays　the　ground　for　parallelizing　unified　search　and　reasoning　at　Web　scale.　©　2009　Springer-Verlag.