Ukwengeza isivinini sokuthuthukisa isivinini, ama-matematics we-array kanye nesimo sokuzivocavoca nge-GPU ku-NVIDIA Tesla P40 (24 GB VRAM, Pascal architecture). Amaseva we-GPU angeke akwazi uku-oda; xhumana nathi ukuze uqinisekiswe uma bekhona.
$ pip install cuml-cu12 xgboost cudf-cu12
# Isibonelo sokufaka umyalo
Ukufunda kwemishini ekhawulelwe yi-GPU-isebenzisa i-CUDA ukusheshisa ukuqeqeshwa nokubikezela. Amathala encwadi afana ne-XGBoost ne-CuPy angasebenzisa i-GPU; i-NVIDIA RAPIDS idinga ama-GPUs amasha kunawo wonke ama-Pascal P40.
Uqeqesho lwe-gradient oluthuthukisa amamodeli ku-GPU.
Ama-arrays ahambisana ne-NumPy asebenza ku-GPU.
Uqeqesho lwezimo ze-neural kanye nezimo ezijwayelekile kulowo mhlinzeki.
Faka amafomethi we-library adinga ukuwasebenzisa ipayipi lakho.
Machine Learning ingasebenzisa i-NVIDIA GPU ukusheshisa umsebenzi wayo. VPS.org amaseva we-GPU akhona ukucela; xhumana nathi ukulalela uma bekhona. Machine Learning yi-GPU-ekhawulelwe umsebenzi ojwayelekile. Qinisekisa ukuthi isofthiwe yakho inezixhaso ze-CUDA futhi ukuthi umshayeli wakho / ama-runtime versions alingana nezidingo zomsebenzi we-Machine Learning.
Amaseva we-GPU akhona ukucela okwamanje. Namuhla ungasebenzisa i-Machine Learning ku-CPU ejwayelekile, lapho isebenza khona ngokucophelela kunakwi-GPU: SSH ngaphakathi bese usebenzisa i-pip install cuml-cu12 xgboost cudf-cu12.
Izidingo ze-VRAM ze-Machine Learning 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-Machine Learning ngaphakathi kwe-RAM ne-storage yeseva.
Yonke isisebenzisi se VPS.org sifika sigcwele ukungena kwe-root SSH, ngakho ungafaka ama-driver, ama-library ne Machine Learning 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 Machine Learning ezidingayo wena.
Yebo. Amaseva we-VPS.org asebenza ngama-machines aqhubekayo, hhayi izimo ezihambayo: amamodeli we-Machine Learning, izilungiselelo nedatha zihlala ku-SSD yokugcina yeseva kuze kube ucima.
Gcina idatha esebenza kuseva ye-SSD ukuze ufinyelele ngokushesha ngesikhathi se-Machine Learning, 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-Machine Learning 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 Machine Learning. 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.