Maxay tirada A100 PCIE FP32 uga hooseysaa kaadhadhka qaar ee RTX?

Tirada 15.6 TFLOPS waa FP32 caadi ah. Inta badan barashada qoto dheer (deep learning) waxay ku shaqeysaa BF16 ama FP16 mixed precision, adeegsiga LLM-kana waxaa inta badan xaddida xawaaraha xusuusta (memory bandwidth), halkaas oo 1313 GB/s ee A100 PCIE uu aad uga sarreeyo kaadhadhka caadiga ah ee Ampere.

Moodellada LLM ee ku habboon 40 GB oo VRAM ah waa kuwee?

Sida caadiga ah, miisaanka 16-bit wuxuu qaataa qiyaastii 2 GB bilyankii kasta oo cabbir ah (billion parameters), markaa moodellada 13B way ku habboon yihiin iyagoo weliba meel u reebaya kaydka KV (KV cache). Moodellada 30B–34B waxay ku habboonaan karaan marka la dhimo (quantized) ilaa 4 ama 8 bits. Moodellada 70B waxay u baahan yihiin kaadh 80 GB ah sida A800 PCIE ama H100.

Waa maxay farqiga u dhexeeya A100 PCIE iyo A100 SXM4?

Labaduba waxay wataan 40 GB, 15.6 TFLOPS FP32 iyo 1313 GB/s. Kaadhka PCIE wuxuu ku shaqeeyaa xaddid koronto oo ah 250 W halka SXM4 uu yahay 400 W, taasoo siinaysa SXM4 awood dheeraad ah oo xakamaynta kulaylka ah marka uu jiro culeys shaqo oo joogto ah.

Sideen server A100 PCIE ah uga bilaabaa Cloudj?

Dooro template sida PyTorch, vLLM ama Ollama, ka xulo qaabeynta A100 PCIE liiska tooska ah oo xaqiiji qiimaha. Ku xirnow adigoo isticmaalaya SSH ama terminal-ka browser-ka; lacag-bixinta saacadlaha ah awgeed, server la damiyay waxaa laga qaadaa oo keliya lacagta disk-igiisa.

GPU Cloud · NVIDIA · Ampere

Kiro GPU-ga NVIDIA A100 PCIE oo wata 40 GB VRAM

Ka kireyso server-yada cloud GPU ee A100 PCIE saacad kasta Cloudj: 40 GB VRAM, qaab-dhismeedka Ampere iyo qiyaastii 1313 GB/s oo xawaaraha xusuusta ah (memory bandwidth) ee shaqooyinka tababarka iyo LLM. Waa tallaabada xog-kaydiyaha (datacenter) ee dhabta ah ee loogu talagalay injineerrada ML ee moodelladoodu aysan hadda ku filnayn kaadhka ciyaaraha (gaming card), iyadoo leh 15.6 TFLOPS FP32, xadka awoodda oo ah 250 W iyo awoodda xisaabinta ee 8.0. Ka bilow template-yada PyTorch, vLLM ama Unsloth, dooro qaabeynta tooska ah oo ku xirnow SSH.

Kireyso A100 PCIE Dhammaan GPU-yada

Faahfaahinta farsamo ee A100 PCIE

VRAM GPU kasta

40 GB

Qaab-dhismeedka

NVIDIA Ampere

Awoodda xisaabinta (Compute capability)

Xisaabinta FP32

≈ 15.6 TFLOPS

Xawaaraha xusuusta (Memory bandwidth)

≈ 1313 GB/s

Xadka awoodda korontada

250 W

Qiyamka ay soo sheegeen bixiyaha kaabayaasha ee mashiinnada hadda liiska ku jira; waxqabadka dhabta ahi wuu ku kala duwanaan karaa mashiin kasta.

Habaynta tooska ah iyo qiimaha A100 PCIE

Kaydka iyo qiimaha tooska ah, oo si joogto ah loo cusbooneysiiyo. Qiimaha ugu dambeeya waxaa la xaqiijiyaa ka hor intaadan dalban.

Kireyso hadda

Waxa aad ku dhex wadi karto cloud GPU-ga A100 PCIE

Ku shaqaysii moodellada 13B–34B adigoo isticmaalaya vLLM

40 GB waxay qaadaysaa moodelka 13B ee 16-bit ah ama moodelka heerka 30B ee la dhimay (quantized), 1313 GB/s-na waxay si joogto ah u waddaa soo saarista token-ka marka ay jiraan codsiyo isku mar ah.

Hufidda (fine-tuning) ee LoRA iyo QLoRA

U habee oo ku tababar moodellada luqadda ee 7B–13B xogtaada adigoo adeegsanaya Unsloth ama PyTorch caadi ah oo ku shaqaynaya BF16, adigoon ku qasbanayn inaad ciriiriso cabbirka xurmada (batch size).

Tababarka moodellada noocyada badan (mixed-precision)

Ku tababar moodellada aragga (vision), hadalka ama xogta jadwalka ah (tabular) BF16 adigoo isticmaalaya kaadh xog-kaydiye oo deggan intii aad kireysan lahayd buuxda node multi-GPU ah.

Embeddings iyo odoroska xurmooyinka (batch inference)

Dukumentiyo aad u tiro badan ku dhex mari moodellada embedding ama soocidda (classification) hal habeen gudaheed, ka dibna tirtir server-ka marka shaqada dufcadda ahi dhammaato.

A100 PCIE ma yahay GPU-ga ku habboon culeyska shaqadaada?

Dooro A100 PCIE 40 GB marka culeyska shaqadaadu uu ka bato xadka xusuusta ee GPU-yada caadiga ah ee macaamiisha (consumer GPUs) ayna u baahan yihiin qalab xog-kaydiye oo xawaarihiisu sarreeyo. U weecqo GPU yar oo macaamiil ah haddii aad u baahan tahay shaqo fudud (inference), ama u gudub nooc xog-kaydiye oo leh VRAM ka sarreeya haddii moodelladaada aan la dhimin ama xurmooyinkaagu ay ka bataan 40 GB.

A100 PCIE vs cloud GPU-yada la midka ah

GPU	VRAM GPU kasta	Xisaabinta FP32	Xadka awoodda korontada
NVIDIA A100 PCIE	40 GB	≈ 15.6 TFLOPS	250 W
NVIDIA A100 SXM4	40 GB	≈ 15.6 TFLOPS	400 W	Faahfaahin →
NVIDIA A40	45 GB	≈ 29.9 TFLOPS	300 W	Faahfaahin →
NVIDIA L40S	45 GB	≈ 73.3 TFLOPS	350 W	Faahfaahin →
NVIDIA Tesla P40	24 GB	≈ 9.4 TFLOPS	250 W	Faahfaahin →

Cloud GPU-ga A100 PCIE: su'aalaha inta badan la isweydiiyo

Kireyso cloud GPU-ga A100 PCIE saacaddii

Dooro template, xulo qaabeyn toos ah, kuna xirnow SSH ama terminal-ka browser-ka. Lacag-bixintu waxay joogsanaysaa marka aad tirtirto GPU-ga.

Kireyso A100 PCIE Dhammaan GPU-yada