Overview
Nzira yekuparadzanisa masvomhu mukati meimwe neural-network layer kune akawanda maGPU saka modhi yakakurisa kune imwe mudziyo inogona kuramba ichimhanya. Izvo zvine basa nekuti mamodheru emuganho ane mazana emabhiriyoni emaparamita ayo hapana imwechete GPU inogona kubata kana kuverenga nekukurumidza zvakakwana ega.
Tensor Parallelism yeMakuru Models chivakwa chekuvaka chinobata mhando yemhando, mutengo wezvivakwa, latency, uye kuvimbika pachiyero.
Deep Dive
Tensor parallelism (inonziwo intra-layer model parallelism) shards uremu hwemunhu matrices paGPUs pane kuisa maturu akazara pamidziyo yakasiyana. Mushanduri, iyo hombe matrix kuwanda-kutarisisa fungidziro uye yekudyisa-mberi MLP-yakakamurwa: semuenzaniso, iyo MLP yekutanga huremu matrix inogovaniswa nemakoramu uye yechipiri nemitsara, saka yega yega GPU inoverengera chidimbu uye imwe chete-kuderedza inosanganisa mhedzisiro. Kutarisa kunopatsanurwa misoro, neGPU yega yega inobata subset. Nekuti yega yega GPU inoita chikamu chega rega rega panguva imwe chete, tensor parallelism inoderedza per-GPU ndangariro uye inomhanyisa compute, asi inoda kazhinji, yakakwirira-bandwidth kutaurirana pakati peGPU yega yega. Ndokusaka ichiwanzovharirwa mukati menode yakabatana neNVLink, uye yakasanganiswa nepombi uye data parallelism yekudzidziswa kwakakura kwazvo uye kushumira mabasa.
Technical Insight
Iwo manomano, anofarirwa neMegatron-LM, ari kusarudza zvikamu zvekuparadzanisa saka kutaurirana kushoma. Kupatsanura yekutanga MLP matrix column-huchenjeri kunoita kuti GPU yega yega ishandise iyo isiri-linearity munharaunda pasina sync; kupatsanura mutsara wechipiri-huchenjeri zvinoreva zvinobuda zvinongoda imwe chete-kudzikisa kuti iite chidimbu mhedzisiro. Imwe neimwe nhanho nekudaro inounza anenge maviri ese-anoderedza (mberi) uye maviri (kumashure). Nekuti aya akaunganidzwa anoitika yega yega, latency inotonga-saka tensor parallelism inogara kuseri kwekukurumidza intra-node zvinongedzo seNVLink pane inononoka inter-node network.
Mastering Tensor Parallelism yeMakuru Models
Nzira yekuparadzanisa masvomhu mukati meimwe neural-network layer kune akawanda maGPU saka modhi yakakurisa kune imwe mudziyo inogona kuramba ichimhanya. Izvo zvine basa nekuti mamodheru emuganho ane mazana emabhiriyoni emaparamita ayo hapana imwechete GPU inogona kubata kana kuverenga nekukurumidza zvakakwana ega. Tensor Parallelism yeMakuru Models chivakwa chekuvaka chinobata mhando yemhando, mutengo wezvivakwa, latency, uye kuvimbika pachiyero. Kuvaka kunzwisisa kwakadzama, tora Tensor Parallelism yeMakuru Mamodheru semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvinodikanwa, kujekesa fungidziro, uye patsanura izvo system inogona kuita nekuvimbika kubva kune ichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Tensor Parallelism yeMakuru Models inokwirisa zvivakwa, data, uye sarudzo dzezvivakwa zvinopesana nekuvimbika uye mutengo. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore. Panguva imwecheteyo, Kukwirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore.
Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete.
Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira.
Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Kudzidzira 175B-parameter modhi nekugovanisa huremu hwega hwega matrices kuyambuka 8 GPUs mune imwe NVLink-yakabatana node uchishandisa Megatron-LM.
Kushandira 70B-parameter chat modhi muvLLM ine tensor_parallel_size=4 kuti huremu hukwane pamaGPU mana uye pindura munguva chaiyo.
Kupatsanura kutarisisa kwekushandura kunotungamira muGPUs kuitira kuti mudziyo wega wega uverenge subset, wozobatanidza zvinobuda kune inotevera layer.
Kubatanidza tensor parallelism mukati me node uye pombi parallelism munzvimbo dzese kudzidzisa matrillion-parameter modhi pamasumbu makuru eGPU.
Maitiro Ekuita
Tensor Parallelism yeMakuru Models mukuita
Kudzidzira 175B-parameter modhi nekugovanisa huremu hwega hwega matrices kuyambuka 8 GPUs mune imwe NVLink-yakabatana node uchishandisa Megatron-LM.
Kudzidzira 175B-parameter modhi nekugovanisa huremu hwega hwega matrices mhiri kwe8 GPUs mune imwe NVLink-yakabatana node uchishandisa Megatron-LM Matimu anowanzo kuwana mhedzisiro iri nani kana vachitsanangudza mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Tensor Parallelism yeMakuru Models mukuita
Kushandira 70B-parameter chat modhi muvLLM ine tensor_parallel_size=4 kuti huremu hukwane pamaGPU mana uye pindura munguva chaiyo.
Kushandira 70B-parameter chat modhi muvLLM ine tensor_parallel_size = 4 kuitira kuti huremu hukwane pamaGPU mana uye kupindura munguva chaiyo Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura mhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Tensor Parallelism yeMakuru Models mukuita
Kupatsanura kutarisisa kwekushandura kunotungamira muGPUs kuitira kuti mudziyo wega wega uverenge subset, wozobatanidza zvinobuda kune inotevera layer.
Kupatsanura kutarisisa kweshanduko kunotungamira muGPUs kuitira kuti mudziyo wega wega uverenge chidimbu, wobva wabatanidza zvinobuda zveiyo inotevera layer Matimu anowanzo kuwana mhedzisiro iri nani kana vachitsanangudza hunhu kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Tensor Parallelism yeMakuru Models mukuita
Kubatanidza tensor parallelism mukati me node uye pombi parallelism munzvimbo dzese kudzidzisa matrillion-parameter modhi pamasumbu makuru eGPU.
Kubatanidza tensor parallelism mukati me node uye pombi parallelism munzvimbo dzese kudzidzisa matrillion-parameter modhi pamapoka makuru eGPU Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye kukanganisa mutengo nekufamba kwenguva.
Njodzi & Guardrails
Kugadzirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba.
Infrastructure uye mari yekugadzirisa inowanzotarisirwa pasi.
Chengetedzo uye kucherechedzwa mapundu anogona kukura sezvo masisitimu anowedzera kuoma.
Implementation Roadmap
Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa.
Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Benchmark pasi pechokwadi mutoro uye data mamiriro.
Benchmark pasi pechokwadi mutoro uye data mamiriro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro.
Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera.
Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.