Me ya sa lambar FP32 ta A100 PCIE ta fi ta wasu katunan RTX ƙanƙanta?

Lambar 15.6 TFLOPS tana nufin ainihin FP32 ne kawai. Yawancin deep learning yana gudana ne a cikin mixed precision na BF16 ko FP16, kuma yawanci inference na LLM yana samun cikas ne daga bandwidth na ƙwaƙwalwa, inda 1313 GB/s na A100 PCIE ya yi wa katunan Ampere na yau da kullum fintinkau nesa ba kusa ba.

Waɗanne LLMs ne ke shiga cikin 40 GB na VRAM?

A ƙa'idar lissafi, nauyin 16-bit yana ɗaukar kusan 2 GB a kowace siga biliyan ɗaya, don haka model na 13B suna shiga tare da samun sarari don KV cache. Model na 30B–34B suna shiga idan an yi musu quantized zuwa bits 4 ko 8. Model na 70B kuma suna buƙatar katin 80 GB kamar A800 PCIE ko H100.

Menene bambanci tsakanin A100 PCIE da A100 SXM4?

Dukansu an lissafa su da 40 GB, 15.6 TFLOPS FP32 da 1313 GB/s. Katin PCIE yana aiki a iyakar ƙarfin wuta na 250 W yayin da SXM4 ke aiki a 400 W, wanda ke ba SXM4 ƙarin damar jure zafi a ƙarƙashin aiki mai tsanani na dogon lokaci.

Ta yaya zan buɗe sabar A100 PCIE a Cloudj?

Zaɓi samfuri kamar PyTorch, vLLM ko Ollama, zaɓi tsarin A100 PCIE daga jerin da ke akwai yanzu sannan ka tabbatar da farashin. Haɗa ta hanyar SSH ko kuma terminal na browser; tare da lissafin kuɗi na sa'a-sa'a, sabar da aka tsayar ana biyan kuɗin ma'ajiyar disk ɗinta kawai.

GPU Cloud · NVIDIA · Ampere

Yi hayar NVIDIA A100 PCIE GPU mai 40 GB VRAM

Yi hayar sabar cloud GPU na A100 PCIE a duk sa'a a Cloudj: 40 GB VRAM, tsarin gine-ginen Ampere da kuma kusan 1313 GB/s na bandwidth na ƙwaƙwalwa don ayyukan LLM da horarwa. Wannan shi ne mataki mai inganci na datacenter ga injiniyoyin ML waɗanda model ɗinsu ba sa iya shiga katin gaming, tare da 15.6 TFLOPS FP32, iyakar ƙarfin wuta na 250 W da compute capability 8.0. Fara daga samfurin PyTorch, vLLM ko Unsloth, zaɓi tsarin da kake so kai tsaye sannan ka haɗa ta hanyar SSH.

Yi hayar A100 PCIE Duk GPUs

Bayanan fasaha na A100 PCIE

VRAM a kowace GPU

40 GB

Ginin fasaha

NVIDIA Ampere

Ikon lissafi (Compute capability)

Lissafin FP32

≈ 15.6 TFLOPS

Gudun ƙwaƙwalwa (Bandwidth)

≈ 1313 GB/s

Ƙayyadaddun wutar lantarki

250 W

Ƙimomin da mai samar da kayan aiki ya bayar don na'urorin da aka jera a yanzu; ainihin aikin ya bambanta dangane da na'ura.

Tsare-tsare da farashin A100 PCIE na yanzu

Kayan da ke akwai da farashin kai tsaye, ana sabunta su akai-akai. Ana tabbatar da farashin ƙarshe kafin ka yi oda.

Yi haya yanzu

Abubuwan da za ka iya gudanarwa a kan cloud GPU na A100 PCIE

Bayar da hidimar model na 13B–34B tare da vLLM

40 GB yana ɗaukar model na 13B a cikin 16-bit ko kuma model ɗin rukunin 30B da aka yi wa quantized, sannan 1313 GB/s yana tabbatar da ci gaba da saurin fitar da token a lokacin buƙatu masu yawa a lokaci ɗaya.

Gyaran fine-tuning na LoRA da QLoRA

Yi fine-tuning ga samfuran yare na 7B–13B akan bayanan kanku ta hanyar Unsloth ko ainihin PyTorch a cikin BF16, ba tare da matse girman batch don ya shiga ba.

Ayyukan horarwa na mixed-precision

Horar da samfuran vision, sauti ko bayanan tabular a cikin BF16 akan ingantaccen katin datacenter maimakon yin hayar cikakkiyar kumburin multi-GPU.

Embeddings da batch inference

Tura manyan tarin takardu ta cikin samfuran embedding ko rarrabewa cikin dare sannan ka goge sabar da zarar an gama aikin batch ɗin.

Shin A100 PCIE ita ce GPU da ta dace da aikinku?

Zaɓi A100 PCIE 40 GB lokacin da nauyin ayyukanku ya wuce iyakar ƙwaƙwalwar GPUs na yau da kullum kuma yake buƙatar kayan aikin datacenter mai babban bandwidth. Zaɓi ƙaramin GPU na yau da kullum don inference maras nauyi, ko kuma haura zuwa samfurin datacenter mai ƙarin VRAM idan model ɗinku marasa quantized ko girman batch ɗinku ya wuce 40 GB.

A100 PCIE idan aka kwatanta da sauran cloud GPU

GPU	VRAM a kowace GPU	Lissafin FP32	Ƙayyadaddun wutar lantarki
NVIDIA A100 PCIE	40 GB	≈ 15.6 TFLOPS	250 W
NVIDIA A100 SXM4	40 GB	≈ 15.6 TFLOPS	400 W	Cikakken bayani →
NVIDIA A40	45 GB	≈ 29.9 TFLOPS	300 W	Cikakken bayani →
NVIDIA L40S	45 GB	≈ 73.3 TFLOPS	350 W	Cikakken bayani →
NVIDIA Tesla P40	24 GB	≈ 9.4 TFLOPS	250 W	Cikakken bayani →

Cloud GPU na A100 PCIE: tambayoyin da aka fi yi

Yi hayar cloud GPU na A100 PCIE a kowace sa'a

Zaɓi samfuri, zaɓi tsari na kai tsaye, sannan ka haɗa ta SSH ko terminal na browser. Caji na tsayawa da zarar ka goge GPU ɗin.

Yi hayar A100 PCIE Duk GPUs