GPUs tsa NVIDIA tse khethehileng le ho kena ka ho feletseng ha tšepe. Ho ruta li-models, ho sebetsana le ho utloahala, ho etsa video, le ho potlakisa ho kopitsa ka litsebi ka kopo.
+-------------------------+
| NVIDIA-SMI 550.54.15 |
| Driver: 550.54.15 |
| CUDA Version: 12.4 |
+-------------------------+
| GPU Name | Mem |
| 0 Tesla P40 | 24GB |
+-------------------------+
| GPU Util: 0% |
| Memory: 0MiB / 24576MiB|
+-------------------------+
$ python train.py --model llama
Loading model... _
GPUs tse khethehileng tsa NVIDIA le ho feta PCIe ho fihlela katleho e phahameng
Re ntse re tsoela pele ho ntlafatsa GPU ea rona. Li-models tse ling tsa NVIDIA GPU tse nang le VRAM e phahameng le li-architectures tse ncha li tla fumaneha kapele.
U hloka GPUs tsa boleng ba khoebo (A100, H100) kapa li-GPU tse ngata? Ikopanye le rona ho bua ka litlhoko tsa hau.
Ho tloha ho ithuta marang-rang a neuron ho isa ho ho etsa liketsahalo tsa 3D, GPU VPS e sebetsana le tsohle
Ho ithuta ka hohle ho sebelisa PyTorch, TensorFlow, kapa JAX. Ho hlophisa ka nepo li-models tsa puo e kholo joalo ka LLaMA, Mistral, le Stable Diffusion ka lisebelisoa tsa GPU tse khethehileng.
Qhobosha →E sebelisa li-models tsa AI ho hlahisa le ho lekola GPU e tlase. E fana ka LLMs, ho theha litšoantšo, ho tsebahala ha puo, le ho bona li-API tsa khomphutha ka boholo.
Qhobosha →Ho potlakisa ho fetolela video ka NVENC, ho etsa liketsahalo tsa 3D ka Blender kapa Maya, le ho sebetsana le li-pipelines tsa litaba tse nang le botsitso bo phahameng ka ho kenya li-encoding tse potlakileng tsa GPU.
Qhobosha →Li-electrode tsa tšepe, li-electrode tsa tšepe, li-electrode tsa tšepe, li-electrode tsa tšepe, li-electrode tsa tšepe, li-electrode tsa tšepe, li-electrode tsa tšepe, li-electrode tsa tšepe.
Qhobosha →Ho potlakisa li-pipelines tsa data ka RAPIDS, cuDF, le cuML. Ho sebetsana le li-dataset tse kholo, ho sebetsana le li-analytics tse potlakileng tsa GPU, le ho theha li-workflows tsa ho sebetsana le data ka nako ea 'nete.
Qhobosha →E theha le ho iterate ka li-application tsa AI ka li-notebooks tsa Jupyter, VS Code remote, le li-environments tsa nts'etsopele ea CUDA e felletseng. Prototype ka potlako ka li-resources tsa GPU tse etselitsoeng.
Qhobosha →PCIe e kopantsoeng kapele e bolela hore ho na le ho se be le ho feta ho Virtualization. Kode ea hau e bua kapele ho GPU hardware.
Ha ho na li-reservations tse thata kapa li-calls tsa thekiso. Khetha GPU ea hau, khetha OS,'me u e sebelise ka metsotsoana.
Lichelete tsa khoeli le khoeli ntle le likonteraka tsa ho koala. E-ba le li-GPU tse ngata ha u hloka,'me u li behe ka tlase ha u sa li hloka.
kenya leha e le efe framework, driver version, kapa CUDA toolkit. Setsi sa hau, melao ea hau. SSH ho kena ho tloha letsatsing la pele.
Litlhahiso tse hlophisitsoeng pele bakeng sa li-frameworks tse tsebahalang tsa AI/ML, lisebelisoa tsa ho etsa, le li-application tse potlakileng tsa GPU
Lintlha tsohle tseo u hlokang ho li tseba ka ho amohela GPU VPS
GPU VPS ke sephutheloana sa marang-rang se nang le NVIDIA GPU hardware. E fana ka ts'ebetso e ts'oanang le VPS e tloaelehileng empa e na le bokhoni bo matla ba ho sebetsana le AI / ML, ho ithuta, ho etsa le ho sebetsa ka likhomphutha tsa litsebi.
Kajeno re fana ka NVIDIA Tesla P40 GPUs le 24GB ea VRAM e le 'ngoe. Li-GPU tsena li atlehile ho AI / ML inference, model fine-tuning, video transcoding, le likhomphutha tsa litsebi. Li-models tsa GPU tse ling li tla eketsoa ha re eketsa liinfrastukture tsa rona.
GPU passthrough e fana ka VPS ea hau ka ho toba, ho kena ka ho toba ho hardware ea GPU. Ho fapana le GPU e arolelanoeng kapa e virtualized, u tla fumana ts'ebetso e felletseng ea GPU ntle le overhead. Likopo tsa hau li sebetsana le GPU joalo ka ha li ne li tla e etsa ka mochini o hlophisitsoeng.
GPU VPS li ka hlaha le Ubuntu le khetho ea ho ba le NVIDIA drivers le CUDA toolkit e kentsoeng pele. U ka kenya mofuta oa driver oa hau o ratoang ka letsoho. Re fana ka litokomane bakeng sa ho kenya li-frameworks tse tsebahalang tsa ML joalo ka PyTorch le TensorFlow.
Ee, u ka kenya GPU tse ngata ho VPS e le 'ngoe bakeng sa litšenyehelo tsa mosebetsi tse nang le melemo ea ho ithuta ho feta GPU kapa ho sebetsa ka kotloloho. Ikopanye le sehlopha sa rona sa thekiso bakeng sa li-GPU tse ngata le litheko.
GPU VPS e loketse ho ithuta le ho etsa liteko tsa AI / ML, ho hlophisa ka nepo liteko tsa puo e kholo, ho bona ka komputa, ho ngola le ho etsa livideo, ho etsa liteko tsa litsebi, le ho etsa mosebetsi o mong le o mong o nang le melemo ea matla a ho sebetsa ka mokhoa o ts'oanang.
GPU VPS e lefa ka letsatsi la beke, joalo ka ha li-plans tsa rona tsa VPS li lekanyelitsoe. U lefa feela bakeng sa nako eo seva ea hau e fanoeng ka eona. Ikopanye le rona bakeng sa theko ea hona joale ha re lefa litheko tsa rona tsa GPU.
GPU VPS liketsahalo sebetsa ka GPU-equipped hardware, kahoo ho ntlafatsa ho tloha VPS standard hloka ho fana ka server e ncha. Leha ho le joalo, u ka potlakela ho fetisetsa data ea hau le ho hlophisa. Tlhokomeliso ea rona e ka thusa le ts'ebetso ea ho fetisetsa.
Ee, li-plans tsohle tsa VPS ho kenyeletsoa le GPU VPS li na le ts'ireletso ea DDoS e lekanyelitsoeng, ho fihlella ha root, IPv4 le IPv6, le likarolo tsa ts'ireletso tse tšoanang le tse fanang ka VPS ea rona ea cloud.
GPU VPS e fumaneha le Ubuntu 22.04 LTS le Ubuntu 24.04 LTS, e nang le ts'ehetso e ntle ka ho fetisisa ea NVIDIA. Debian 12 e boetse e tšehetsoa. Re khothaletsa Ubuntu 24.04 LTS bakeng sa ts'ebelisano ea CUDA toolkit e ncha.
Ha ho na ho khetheha. GPU VPS e lefa ka khoeli'me u ka e hlakola nako efe kapa efe. Re lumela ho sebetsa ka ho iketsa, ho se na ho koaloa ha cloud computing.
E etsa feela ak'haonte, khetha GPU VPS configuration, khetha sistimi ea hau ea ts'ebetso,'me u e sebelise. Setsi sa hau sa GPU se tla ba se loketse ka metsotsoana le ho fihlella root e felletseng le GPU ea hau e fumanehang ka nvidia-smi.
Fumana matla a NVIDIA GPU a hlophisitsoeng ka metsotso. Ha ho na li-reservations, ha ho na li-call tsa thekiso.