Sebenzisa i-GPU ku-NVIDIA Tesla P40 (24 GB VRAM, Pascal architecture) ukusiza umsebenzi we-data science ku-Jupyter. Amaseva we-GPU angeke akwazi uku-oda; xhumana nathi ukuze uqinisekiswe uma bekhona.
$ pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0
# Isibonelo sokufaka umyalo
Ulwazi lwedatha olukhawulelwe yi-GPU luya ezindaweni ezinzima zokufaka izilinganiso nezilinganiso zokulinganisa ku-GPU. I-CuPy, XGBoost ne-PyTorch zixhasa i-Pascal P40; i-NVIDIA RAPIDS (cuDF, cuML) idinga i-GPU entsha.
Ama-GPU ahlukanisiwe ne-gradient ethuthukisiwe exhasa ama-Pascal GPUs.
Faka iJupyterLab futhi usebenze ngokuzenzekelayo ku-GPU.
Gcina ama-array amakhulu kwimemori ye-GPU uma usebenza.
Faka izinhlelo ze-PyData stack ezidingayo.
Data Science ingasebenzisa i-NVIDIA GPU ukusheshisa umsebenzi wayo. VPS.org amaseva we-GPU akhona ukucela; xhumana nathi ukulalela uma bekhona. Data Science yi-GPU-ekhawulelwe umsebenzi ojwayelekile. Qinisekisa ukuthi isofthiwe yakho inezixhaso ze-CUDA futhi ukuthi umshayeli wakho / ama-runtime versions alingana nezidingo zomsebenzi we-Data Science.
Amaseva we-GPU akhona ukucela okwamanje. Namuhla ungasebenzisa i-Data Science ku-CPU ejwayelekile, lapho isebenza khona ngokucophelela kunakwi-GPU: SSH ngaphakathi bese usebenzisa i-pip install cudf-cu12 cuml-cu12 jupyterlab && jupyter lab --ip=0.0.0.0.
Izidingo ze-VRAM ze-Data Science zixhomekeke kumodeli kanye nobukhulu beqembu; hlola idatabase yephrojekthi ngezibalo zamanje.
Intengo ye-GPU izoshicilelwa uma izisebenzisi ze-GPU zingasatshalaliswa. Xhumana nathi uma ufuna ukulalela uma lokhu kwenzeke.
Yebo. Yonke iseva ye-VPS.org ifika nge-root access egcwele, ngakho ungasebenzisa ezinye izisetshenziswa kanye ne-Data Science ngaphakathi kwe-RAM ne-storage yeseva.
Yonke isisebenzisi se VPS.org sifika sigcwele ukungena kwe-root SSH, ngakho ungafaka ama-driver, ama-library ne Data Science noma ngabe ufuna.
Akukho umsekeli ofika ngesikhathi sokusebenza se-CUDA noma umqhubi we-NVIDIA ofakwe ngaphambili, futhi ama-servers we-GPU atholakalanga ukuthenga okwamanje. Ungafaka izibuyekezo Data Science ezidingayo wena.
Yebo. Amaseva we-VPS.org asebenza ngama-machines aqhubekayo, hhayi izimo ezihambayo: amamodeli we-Data Science, izilungiselelo nedatha zihlala ku-SSD yokugcina yeseva kuze kube ucima.
Gcina idatha esebenza kuseva ye-SSD ukuze ufinyelele ngokushesha ngesikhathi se-Data Science, futhi ukope izitho eziqediwe (izitho, izizukulwane, izingeniso) ukugcinwa ngaphandle kwe-VPS.org; ama-snapshots nama-backup ahlala ku-storage cluster efanayo.
Ungakhuphula noma iyiphi iseva ye-VPS.org ibe yi-plan enkulu kusuka kwindawo yokulawula; ukushintsha ubukhulu kuqala kabusha futhi ukufakwa kwe-Data Science kudlulisa. Amaseva we-GPU akhona.
Yebo. Amafayela okugcina akhokhelwa angeza-on (ngesonto +30% yentengo yephrojekthi, igcinwe 7 izinsuku; ngeviki +20%, igcinwe 28 izinsuku) futhi ama-snapshots amahhala, okusiza ngaphambi kokuhamba isikhathi eside Data Science. Kokubili kuhlale ku-indawo yokugcina efanayo njengeseva.
Xhumana nosizo ngaphakathi kwezinsuku ezingama-30 zokuthenga kwakho okukuqala ukuze ucele ukubuyiselwa imali. Amaseva we-GPU athengiswe, ngakho-ke akukho sinqumo se-GPU esihlobene.
Ikhono le-GPU lilinganiselwe. Sitshele ngomsebenzi wakho futhi sizophendula ngokutholakala nokuthengwa.