paralelism tensor ngir model yu mag
Benn anam buñu mëna xaajalee math bi ci biir benn reso neuronal ci GPU yu bari suko defee benn model bu rëy lool ci benn aparey mën dox ba leegi.
Résumé
It matters because frontier models have hundreds of billions of parameters that no single GPU can hold or compute fast enough alone.
Plongeur bu xóot
Parallelism tensor (ñu koy woowe itam parallelism model intra-couche) dafay xaaj matrice yu diisaay yi ci GPU yi moo gën ñu def ay couche yépp ci ay aparey yu wuute. Ci biir transformateur, matrix bu mag bi dafay yokk - projection attention ak MLP feed-forward - dañuy xaaj: ci misaal, matrix poids bu njëkk bi ci MLP dañu ko xaaj ci kolon ak ñaareel bi ci ligne, kon GPU bu nekk dafay xayma benn dagg ak benn all-reduce boole ci resultaa yi. Dañu xaaj bàyyi xel ci bopp yi, GPU bu nekk di jëfandikoo benn subset. Ndax GPU bu nekk dafay bokk ci bépp couche ci benn yoon, tensor parallelism dafay wàññi memory bu GPU bu nekk ba noppi gaawal ordinatër bi, waaye dafay laaj jokkoo bu bari, bandwidth bu kawe diggante GPUs couche bu nekk. Loolu moo tax ñu koy faral di tëj ci biir benn node bu NVLink lëkkale, ba noppi boole ci pipeline ak parallelism ci done ngir tàggat yu yaatu lool ak liggéey.
Gis-gis xarala
Kaf gi, Megatron-LM siiwal, mooy tànn dimension xaaj bi suko defee jokkoo bi gëna néew. Séddale matrix MLP bu njëkk bi ci kolon dafay tax GPU bu nekk jëfandikoo nonlinearite ci barab bi te amul sync; xaaj ñaareelu rang-wise dafay tekki ni génne yi soxla nañu benn all-reduce ngir boole ay resultaa yi. Kon couche bu nekk dafay am lu tollu ci ñaari all-reduces (ci kanam) ak ñaar (ci ginaaw). Ndax mbootaay yooyu dañuy am ci bépp etaas, latency mooy ëpp doole - kon parallelism tensor mingi dundu ci ginaaw lëkkalekaay yu gaaw yi ci biir node yu melni NVLink moo gën reso yu gëna néew ci biir node yi.
njeextalu pexe
Njëgg ak budget
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
dogal yu gëna leer
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
Xool kalite
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.
Ëlëgu paralelism tensor ngir model yu mag
Paralelism tensor mingi wéy di nekk lu am solo waaye mingi gëna jaxasoo ak 'paralelism 3D' (tensor + pipeline + done) ba noppi boole ci paralelism eksper ngir xeetu njaxasu-ekspert. Kadre yu melni Megatron-LM, DeepSpeed, ak vLLM ñooy otomatise xaaj bi. Lu GPU di lëkkaloo (NVLink, NVSwitch) ak tissu optik di gëna gaaw, yam ci node-frontière dafay féexal, may grupu tensor yu gëna yaatu. Xaarandil paralelisasioŋ otomatik bu gëna am xel buy tànn dimension shard ak dayo grupu ngir wàññi jokkoog topologie cluster buñ jox.
Doxal ci àdduna dëgg
Taggat ab xeetu paramet 175B ci xaaj matris bu diisaayu couche bu nekk ci 8 GPU ci benn node bu lëkkaloo ak NVLink di jëfandikoo Megatron-LM.
Defar ab xeetu waxtaan bu am 70B ci vLLM ak tensor_parallel_size = 4 suko defee diisaay yi mëna méngoo ak ñeenti GPU yi te tontu ci jamono dëgg.
Séddale boppu transformatër yi ci GPU yi suko defee aparey bu nekk xayma benn subset, ba noppi boole ay sorti ngir layer bi ci topp.
Njaxas paralelismu tensor ci biir node yi ak paralelismu pipeline ci biir node yi ngir tàggat model yu am bilioŋu paramet ci kaw cluster GPU yu mag.
Risk yi ak balustrade yi
Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.
Roadmap ngir samp gi
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
Benchmark ci biir sargal ak done yu dëggu.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.
Weyal di banneexu
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Gis bi ci topp
Model ak paralelismu tuyo
Laaj yi ñuy faral di laaj
What is Tensor Parallelism for Large Models?
Benn anam buñu mëna xaajalee math bi ci biir benn reso neuronal ci GPU yu bari suko defee benn model bu rëy lool ci benn aparey mën dox ba leegi. Dafa am solo ndax model frontier yi amnañu téemeeri milyaari parametre yu benn GPU mënul tëye wala xayma lu gaaw kese.
Lan mooy xaaj paralelism tensor ci GPU yi?
Parallelism tensor (ci biir couche) dafay xaaj matrice yu diis yi ci biir benn couche, kon GPU bu nekk dafay xayma benn wàll ci benn couche bi - wuute ak parallelism pipeline, biy def couche yu mat ci GPU yu wuute.
Ci xaajalug MLP bu nuroo ak Megatron, naka lañuy xaajalee ñaari matris yu diis yi ngir wàññi jokkoo bi?
Séddale matrix bi njëkk ci kolon dafay tax GPU bu nekk jëfandikoo nonlinearite ci barab bi; xaaj ñaareel bi ci ligne yi dafay tekki ni benn-wàññi dafay boole génnug pàrtiel yi—di wàññi synchronisation.
Lu tax ñuy faral di denc paralelism tensor ci benn node?
Bépp couche dafay indi jokkoo bu mbooloo (ñépp-wàññi), kon trafik bu diis, latency-sensitif dafay laaj lëkkalekaay yu gaaw ci biir node yu melni NVLink moo gën reso inter-node yu yeex.
naka lañuy méngale mekaniismu bàyyi xel ci suufu paralelism tensor?
Bopp yiy bàyyi xel ci seen bopp, moo tax dañu leen séddale ci GPU yi—aparey bu nekk dafay xayma yenn bopp ba noppi boole li ñuy génne.
Ban jëf bu mbooloo mooy faral di boole ay resultaa yu xaaj ci paralelism tensor?
All-reduce dafay boole génnekaay yiñ xayma ci GPU bu nekk suko defee ñu déggoo ci njariñu couche bi; loolu dafay am yoon yu bari ci layer bu nekk ci paas yu jëm kanam ak yu ginaaw.