TensorRT ak motëri jàngat
TensorRT mooy bibliotek bu NVIDIA biy dajale ay reso neuronal yuñ tàggat ci ay motër yu gëna gaaw ci GPU yu NVIDIA.
Résumé
It matters because the same model can run 2-6x quicker and cheaper at inference time without changing what it predicts.
Plongeur bu xóot
Benn motëru inference dafay jël model buñu tàggat ba noppi binndaat ko ngir gëna gaaw ci liggéey bi ci hardware biñ bëgga jëfandikoo. TensorRT dafay def lii ci GPU NVIDIA ci jéego yu bari. Dafay def fusion couche, boole ay jëf yu melni convolution, bias-add, ak ReLU ci benn kernel GPU ngir wàññi dem bi ak dikk bi ci mémoire bi. Dafay jëfandikoo etalonnage bu jaar yoon, wàcci ci FP32 ba FP16 wala INT8 (ak FP8 ci Hopper) boole ci baña yàq njub. Dafay def kernel auto-tuning, di benchmarking jëfandikoo lu bari ci layer bu nekk ci sa GPU ndànk ba noppi tànn bi gëna gaaw. Lépp soo ko boolee mu nekk fichier 'moteur' buñ boole ci benn architecture GPU. TensorRT-LLM dafay yokk lii ci cache KV bu am xët, boole ci naaw, ak paralelism tensor ngir xeetu làkk yu mag.
Gis-gis xarala
Gaawaay yi gëna mag ñu ngi bawoo ci ñaari pexe. Kernel fusion dafay dindi dem ak dikk ngir yeexal mémoire global GPU ndax dafay tëye resultaa yi ci diggante yi ci registre yu gaaw ak mémoire buñ bokk. Quantization ci INT8 dafa am ñeenti valeur yu benn FP32 toog, di yokk ñeenti yoon limu arithmétique ci core tensor yi, waaye mingi soxla ensemble done buy etalonnage ngir xayma facteur scaling tensor bu nekk suko defee rang numérique bu wàññeeku bi baña yàq njub. Motër bi dafa jëm ci hardware bi ndax auto-tuning dafay nekk ci kernel yi gëna baax ci core ak memory bi ci GPU bi.
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 TensorRT ak Motëri Njàngat
Motëri inference yi ñu ngi dem ci wàllu gëna néew (FP8, FP4, ak ay pexe yu wuute) ak màndarga yu jëm ci LLM yu melni dekodaas speculatif ak paging KV-cache bu gëna am xel. TensorRT-LLM ak ay konkurent yu melni vLLM ñu ngi booloo ci prefill/decode buñ xaaj ak batching buy wéy. Xaarandi mboolem compilatër bu gëna dëgër (Torch-TensorRT, ONNX), kantite otomatik ak etalonnage manuel bu néew, ak ndimmbal bu yaatu ngir njaxasu-ekspert yi ci yoon ndax liggéey model yu mag yi ci njëg yu yomb nekk na xare bu mag bi ci njëg yi.
Doxal ci àdduna dëgg
Soppi benn xeetu gis-gis mbir YOLO ci benn motër TensorRT INT8 suko defee mu mëna dox ci jamono dëgg ci kaw benn NVIDIA Jetson ci biir benn robot wala benn kamera bu xarañ
Liggéeyukaay xeetu Llama wala Mistral ak TensorRT-LLM di jëfandikoo xeetu naaw ngir yokk ay jeton ci segond bu nekk ci GPU H100 ci backend chatbot
Xaarandi xeetu xàmmee kàddu ak FP16 ngir wàññi latency transcription ci sarwiisu sous-titre
Dajale ab reso buy raññe ay xalaat ci benn motër TensorRT buñ boole ngir mëna jëflante ak ay milioŋ ci laaj ci segond bu nekk ci njëgu GPU bu gëna néew
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
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Laaj yi ñuy faral di laaj
What is TensorRT and Inference Engines?
TensorRT mooy bibliotek bu NVIDIA biy dajale ay reso neuronal yuñ tàggat ci ay motër yu gëna gaaw ci GPU yu NVIDIA. Dafa am solo ndax benn model bi mën na daw 2-6x gëna gaaw te gëna yomb ci waxtu inference te du soppi li muy wax.
Lan mooy jubluwaay bu njëkk ci motëru inferensi bu melni TensorRT?
Motëri inference yi dañuy jël model buñ jota tàggat ba noppi binndaat ko ngir am gaawaay bu gëna mag ci benn hardware; duñu tàggat ay model.
naka la fusion couche di gaawaalee inférence bi?
Fusion dafay boole ay jëf yu melni conv, bias, ak aktivasioŋ ci benn kernel suko defee njariñu digg yi des ci mémoire bu gaaw bi, duñu leen bindaat ci mémoire global bu yeex bi.
Lan moo waral kantite INT8 di soxla ensemble done buñ etalonnage?
Etalonnage dafay doxal ay done yu wuute ci model bi ngir xam facteur scale tensor bu nekk, kon INT8 bu gàtt bi dafay denc distribution valeur yu am solo yi.
Lan moo waral benn motër TensorRT buñ dajale dafay nekk benn architecture GPU kese?
Auto-tuning dafay màndargaal kernel yi ci GPU biñ bëgga jëfandikoo, ba noppi tànn bi gëna baax, suko defee motër bi lëkkaloo ak màndarga yi architecture bi am.
Ban màndarga ci TensorRT-LLM mooy gëna jàppale modeli làkk yu mag yi ci anam wu jaar yoon?
TensorRT-LLM dafay yokk ay njariñ yu jëm ci LLM lu ci melni batching ci biir naaw ak KV-cache ngir yokk limu mëna def ci liggéey yiy génne mbind.