▁algorithms , ▁one ▁is ▁typically ▁interested ▁in ▁asympt otic ▁bounds ▁on ▁the ▁resource ▁consumption ▁( main ly ▁time ▁spent ▁computing ), ▁but ▁the ▁analysis ▁is ▁performed ▁in ▁the ▁presence ▁of ▁multiple ▁processor ▁units ▁that ▁co oper ate ▁to ▁perform ▁comput ations . ▁Thus , ▁one ▁can ▁determine ▁not ▁only ▁how ▁many ▁" steps " ▁a ▁computation ▁takes , ▁but ▁also ▁how ▁much ▁faster ▁it ▁becomes ▁as ▁the ▁number ▁of ▁process ors ▁goes ▁up . ▁Interest ingly , ▁the ▁analysis ▁approach ▁works ▁by ▁first ▁suppress ing ▁( or ▁abstract ing ▁away ) ▁the ▁number ▁of ▁process ors . ▁ ▁The ▁next ▁background ▁paragraph ▁explains ▁how ▁the ▁abstra ction ▁of ▁the ▁number ▁of ▁process ors ▁first ▁emer ged . ▁ ▁A ▁so - called ▁work - time ▁( WT ) ▁( s ometimes ▁called ▁work - depth , ▁or ▁work - span ) ▁framework ▁was ▁originally ▁introduced ▁by ▁Sh ilo ach ▁and ▁V ish kin ▁ ▁for ▁concept ual izing ▁and ▁describing ▁parallel ▁algorithms . ▁ ▁In ▁the ▁W T ▁framework , ▁a ▁parallel ▁algorithm ▁is ▁first ▁described ▁in ▁terms ▁of ▁parallel ▁r ounds . ▁For ▁each ▁round , ▁the ▁operations ▁to ▁be ▁performed ▁are ▁character ized , ▁but ▁several ▁issues ▁can ▁be ▁suppress ed . ▁For ▁example , ▁the ▁number ▁of ▁operations ▁at ▁each ▁round ▁need ▁not ▁be ▁clear , ▁process ors ▁need ▁not ▁be ▁mentioned ▁and ▁any ▁information ▁that ▁may ▁help ▁with ▁the ▁assignment ▁of ▁process ors ▁to ▁jobs ▁need ▁not ▁be ▁account ed ▁for . ▁Second , ▁the ▁suppress ed ▁information ▁is