Sebenzisa i-GPU kwi-NVIDIA Tesla P40 (24 GB VRAM, uyilo lwePascal) lomsebenzi wolwazi lwedatha kwi-Jupyter. Abancedisi be-GPU abakwazi ukuthengwa; qhagamshelana nathi ukuze sikwazisa xa bekhona.
$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0
# Umzekelo wofakelo lomyalelo
I-GPU-ekhawulezayo i-data science ihambisa umqolo onzima kunye nemodeli yobalo kwi-GPU. I-CuPy, XGBoost ne PyTorch ixhasa i-Pascal P40; NVIDIA RAPIDS (cuDF, cuML) ifuna i-GPU entsha.
I-GPU i-array kunye nokuphuculwa kokungathathi hlangothi okuxhasa i-Pascal GPUs.
Faka i-JupyterLab kwaye usebenze ngokunxibelelana kwi-GPU.
Gcina amaqela amakhulu ezinto kuvimba weefayili ze-GPU xa usebenza.
Faka uguqulelo lwe PyData olufunayo.
Data Science inokusebenzisa i NVIDIA GPU ukukhawulezisa umsebenzi wayo. VPS.org GPU abancedisi abafumanekanga ukucela ngoku; qhagamshelana nathi ukuva xa bekhona. Data Science yi GPU- ekhawulezayo yomsebenzi oqhelekileyo. Qinisekisa ukuba udweliso lwenkqubo luxhaswe yi CUDA kwaye ukuba umqhubi wakho / uguqulelo lwexesha lokusebenza luhambelana neemfuno zomsebenzi womsebenzi we Data Science.
Abancedisi be-GPU abafumanekanga ukucela ngoku. Namhlanje ungaqhuba i-Data Science kwi-CPU eqhelekileyo, apho isebenza khona ngokucothayo kune-GPU: SSH ngaphakathi kwaye uqhube i-pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0.
Iimfuneko ze-VRAM ze-Data Science zixhomekeke kwimodeli kunye nobungakanani beqela; khangela ushicilelo lweprojekthi yemifanekiso yangoku.
Ixabiso le-GPU liza kupapashwa xa iiseva ze-GPU zingafunyanwa. Xhulumanisa nathi ukuba ufuna ukuva xa oku kwenzeka.
Ewe. Isincedisi ngasinye se-VPS.org sifika sinee-root access ezipheleleyo, ngoko ungaqhuba ezinye izixhobo kunye ne-Data Science ngaphakathi kwe-RAM yeseva kunye nokugcina.
Yonke i VPS.org umncedisi ifika nge root SSH unikezelo olupheleleyo, ngoko ungafaka abaqhubi, iincwadi ze Data Science nokuba ufuna njani.
Hayi. Akukho mncedisi ufika nexesha lokuqhuba le-CUDA okanye umqhubi we-NVIDIA ofakwe ngaphambili, kwaye abancedisi be-GPU abafumanekanga ukucela ngoku. Ufaka uguqulelo lwe-Data Science olufunayo ngokwakho.
Ewe. Abancedisi be-VPS.org basebenza njengezimatshini ezibonakalayo eziqhubekayo, azikho iziganeko ezikhawulezayo: iimodyuli ze-Data Science, iinkqubo zokumiselwa kwenkqubo kunye nedata zihlala kwi-SSD yokugcina yeseva de uzicime.
Gcina i-data esebenza kwi-SSD yomncedisi ukufikelela ngokukhawuleza ngexesha lokusebenza kwe-Data Science, kwaye ukope i-artifacts egqityiweyo (isisindo, u Generations, i-embeddings) ukugcinwa ngaphandle kwe-VPS.org; iifoto ezikhawulezayo kunye nokhuseleko luhlala kwiqela elinye lokugcina.
Unganyusa nayiphi na iseva ye-VPS.org ibe yinkqubo enkulu ukusuka kwiqela lenjongo yolawulo; ubungakanani obutsha buqala kwakhona kwaye ukufaka kwe-Data Science kugqitha. Iiseva ze-GPU azifumanekanga ngoku.
Ewe. Iindawo zokugcina zihlawulwe zidityaniswe (ngosuku +30% yexabiso lenkqubo, igcinwe iintsuku ezi-7; ngeveki +20%, igcinwe iintsuku ezi-28) kwaye iifoto ezikhawulezayo zikhululekile, eziluncedo phambi kwe Data Science ende iqhuba. Zonke zihlala kwiqela lokugcina elifanayo njengeseva.
Nxibelelana noncedo ngaphakathi kweentsuku ezingama-30 zokuthengiswa kwakho kokuqala ukuze ucele ubuyiselo. Iiseva ze-GPU azithengwanga, ngoko akukho mfuneko yokuthumela i-GPU.
Ubungakanani be-GPU bumiselwe. Sixelele malunga nobunzima bomsebenzi wakho kwaye siza kuphendula ngokufumaneka nokuthengiswa.