Triton Inference Kediska Server

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Maxaa ka dhigaya Triton Inference Server 'qaab-dhismeedka-agnostic'?
   • Hal tusaale ayaa hal mar u adeegi kara moodooyinka PyTorch, TensorFlow, ONNX, TensorRT, iyo dhabarka danbe ee caadada ah hal mar
   • Kaliya waxa ay wadaa matoorada TensorRT
   • Model kasta waxay u beddeshaa Java
   • Waxay u baahan tahay dhammaan moodooyinka in dib loogu tababaro hal qaab
2. Sidee buufiska firfircoon u hagaajiyaa waxqabadka?
   • Adigoo ka baaraandegaya codsi kasta isla markiiba uu yimaado, midba mar
   • Iyada oo la ururinayo codsiyada soo dhawaada si wadajir ah oo hal dufcadood ah GPU-ga
   • Adigoo tirtiraya codsiyada si tartiib tartiib ah u yimaada
   • Adigoo tixraacaya CPU
3. What trade-off can Triton dynamic batching introduce?
   • Every request becomes lower latency regardless of traffic
   • It raises model accuracy by changing the weights
   • Compatible stateless requests may gain throughput while queued requests wait within a configured delay
   • It only works when inference runs on a CPU
4. Muxuu Triton 'model ensemble' (ama qoraalka macquulka ah) kuu ogolaado inaad sameyso?
   • Si wadajir ah u tababar dhowr nooc
   • Siri faylasha qaabka
   • Iska yaree saxnaanta moodeelka
   • Silsilad diyaarinta, ka-fiirsashada, iyo dib-u-habaynta ka-hortagga hal dhuumood oo server-ka ah
5. What does Triton concurrent model execution permit?
   • Multiple models or instances to execute in parallel on the same system, subject to available resources
   • Only one model may run until the server restarts
   • A model to change its weights during each request
   • Requests to bypass the scheduler and share another model output
6. Waa kuwee borotokoollada ay Triton caadi ahaan u soo bandhigto macaamiisha si ay u soo diraan codsiyo faragelin?
   • Kaliya FTP
   • HTTP/REST iyo gRPC
   • Kaliya iimaylka
   • Kaliya Bluetooth
7. Which monitoring interface does the Triton guide say it exposes?
   • A built-in SQL reporting dashboard
   • A browser-only interactive notebook
   • Prometheus metrics
   • A mandatory cloud billing API
8. What should a serving team measure when tuning dynamic batching?
   • Only the largest possible batch size
   • Only average model parameter count
   • Only startup time on an idle server
   • Throughput and latency under representative request traffic