Ingabe i-Tesla P40 ilungele ukuqeqesha amamodeli esimanje?

Hhayi ngempela. I-Pascal ayinawo ama-Tensor Cores futhi ayisekeli i-BF16, kanti ne-throughput yayo ye-FP16 iphansi kakhulu, ngakho ukuqeqesha nge-mixed-precision kuhamba kancane. Yisebenzisele i-quantized inference noma imisebenzi ye-FP32; ekuqeqesheni, ikhadi le-RTX 3090 noma elisha kakhulu lilunge kakhulu.

Imaphi ama-LLM asebenza kahle ku-24 GB?

Amamodeli e-GGUF e-4-bit afika cishe kuma-parameter angu-30B, namamodeli angu-7B–14B ku-8-bit, nge-Ollama noma nge-llama.cpp. Lindela isivinini esilinganiselwe: 257 GB/s inciphisa inani lama-token ngomzuzwana.

Ingabe izinguqulo zamanje ze-PyTorch kanye ne-vLLM zizosebenza ku-Tesla P40?

Kuncike ekwakhiweni (build). I-P40 ine-compute capability engu-6.1 kanti ezinye izakhiwo zakamuva ze-CUDA nama-framework azisawahambeli ama-GPU amadala. Izifanekiso ze-Cloudj zibala inguqulo yazo encane ye-CUDA futhi zinikeza kuphela ama-GPU ahambisanayo.

Tesla P40 vs RTX 3090: yikuphi ukwehluka nokuncama?

Zombili zine-24 GB. I-RTX 3090 ikalwe ku-35.4 TFLOPS kanye no-805 GB/s inama-Tensor Cores esimanje, ngakho iyashesha kakhulu. I-P40 inketho endala lapho ukuthola i-24 GB kubaluleke kakhulu kunesivinini.

GPU Cloud · NVIDIA · Pascal

Qasha i-NVIDIA Tesla P40 GPU ene-24 GB VRAM

Qasha amaseva e-cloud GPU e-Tesla P40 ngehora ku-Cloudj: 24 GB VRAM ku-NVIDIA Pascal enomthamo olinganiselwa ku-9.4 TFLOPS FP32 kanye ne-bandwidth yememori engu-257 GB/s. Kuyindlela elula nengabizi yokuthola imemori engu-24 GB ye-quantized LLM inference, amaphrojekthi okuzilibazisa kanye nomsebenzi wakudala we-CUDA, ngaphansi komkhawulo wamandla kagesi ongu-250 W. Hlola izidingo ze-CUDA zesifanekiso, qala ngesithombe se-Ollama noma se-PyTorch bese uxhuma nge-SSH.

Qasha i-Tesla P40 Wonke ama-GPU

Imininingwane ye-Tesla P40

VRAM nge-GPU ngayinye

24 GB

Architecture

NVIDIA Pascal

Compute capability

6.1

Ukubala kwe-FP32

≈ 9.4 TFLOPS

I-bandwidth yememori

≈ 257 GB/s

Umkhawulo wamandla

250 W

Amanani abikwa umhlinzeki wengqalasizinda yemishini ebalwe ohlwini njengamanje; ukusebenza kwangempela kuyehluka ngomshini ngamunye.

Izilungiselelo zamanje nezintengo ze-Tesla P40

Isitoko esibukhoma nezintengo, kubuyekezwa ngokuqhubekayo. Intengo yokugcina iqinisekiswa ngaphambi kokuba u-ode.

Qasha manje

Ongakusebenzisa ku-cloud GPU ye-Tesla P40

Ama-LLM e-quantized nge-Ollama

I-24 GB ikwazi ukuthwala amamodeli e-GGUF afika cishe kuma-parameter angu-30B ku-4-bit, okuwukusetshenziswa okuhle kakhulu kwe-P40 namuhla.

Ingxoxo eyimfihlo kanye nama-prototype e-RAG

Sebenzisa i-Ollama nge-Open WebUI ukwenza umsizi oyimfihlo wamadokhumenti akho ngaphandle kokuthumela idatha ku-API.

Imisebenzi yakudala ye-FP32

Sebenzisa amakhodi amadala e-CUDA, ukulingisa kanye nokuqeqeshwa kwe-FP32 okungancikile kuma-Tensor Cores.

Ukufunda nomsebenzi wesikole

Thola ulwazi olusebenzayo ngamaseva e-GPU, ama-driver kanye ne-CUDA kumemori engu-24 GB yocwaningo oluncane.

Ingabe i-Tesla P40 iyi-GPU efanele umsebenzi wakho?

Khetha i-Tesla P40 uma isidingo sakho esiyinhloko kuyi-24 GB ye-VRAM ye-inference edinga imemori eningi noma imisebenzi yokuthuthukisa lapho amandla amadala e-Pascal anele. Khetha i-GPU entsha noma enkulu kakhulu uma udinga i-bandwidth yememori ephezulu noma ukusheshisa kwesimanje kwe-tensor ekuqeqesheni okunzima, noma i-GPU encane uma umsebenzi wakho usebenzisa imemori encane.

Tesla P40 uma iqhathaniswa nama-cloud GPU afanayo

GPU	VRAM nge-GPU ngayinye	Ukubala kwe-FP32	Umkhawulo wamandla
NVIDIA Tesla P40	24 GB	≈ 9.4 TFLOPS	250 W
NVIDIA L4	22 GB	≈ 24.2 TFLOPS	72 W	Imininingwane →
NVIDIA Tesla V100	16 GB	≈ 12.5 TFLOPS	300 W	Imininingwane →
NVIDIA A100 PCIE	40 GB	≈ 15.6 TFLOPS	250 W	Imininingwane →
NVIDIA A100 SXM4	40 GB	≈ 15.6 TFLOPS	400 W	Imininingwane →

I-cloud GPU ye-Tesla P40: imibuzo evame ukubuzwa

Qasha i-cloud GPU ye-Tesla P40 ngehora

Khetha ithempulethi, khetha izilungiselelo zamanje bese uxhuma nge-SSH noma itheminali yesiphequluli. Ukukhokhisa kuyama uma ususa i-GPU.

Qasha i-Tesla P40 Wonke ama-GPU