H100 PCIE ko A100: shin ya dace a haɓaka?

Bisa bayanan da aka lissafa, H100 PCIE na da ƙwaƙwalwa sau biyu na A100 40 GB, kusan ninki 2.6 na FP32 (41 idan aka kwatanta da 15.6 TFLOPS) da ƙarin bandwidth (1760 idan aka kwatanta da 1313 GB/s). Ayyukan da ke buƙatar ƙarfin lissafi ko ƙwaƙwalwa sosai suna kammala da sauri, wanda hakan ke rage nauyin farashin kowace sa'a mafi girma.

Yaya H100 PCIE yake idan aka kwatanta da H100 SXM?

Dukansu suna da 80 GB. An lissafa H100 SXM a 53.5 TFLOPS da 2869 GB/s tare da iyakar 700 W, don haka yana da sauri sosai; H100 PCIE a 350 W shine zaɓi mai ƙarancin amfani da wuta ga ayyukan da suka dace da ƙarfinsa.

Wane girman samfura ne ke dacewa a kan 80 GB?

Kusan sigogi 34B a 16-bit tare da sararin mahallin aiki (context headroom), ko samfuran rukunin 70B da aka yi wa quantized zuwa 4 bits. Ga 16-bit 70B, duba 140 GB H200 NVL.

Yaya saurin da zan iya kunna H100 PCIE a Cloudj?

Zaɓi template, ɗauki H100 PCIE da ke akwai a jerin kai tsaye sannan ka tabbatar da farashin; ana ƙirƙirar server daga kuɗin asusunka kuma ka haɗu ta hanyar SSH ko terminal na browser.

GPU Cloud · NVIDIA · Hopper

Yi Hayar GPU ta NVIDIA H100 PCIE Mai 80 GB VRAM

Yi hayar H100 PCIE GPUs a kowace sa'a a Cloudj: 80 GB VRAM a kan NVIDIA Hopper, kusan 41 TFLOPS FP32 da 1760 GB/s memory bandwidth don horarwa da LLM inference. Ita ce mashigar Hopper ga ƙungiyoyin AI da ke son 80 GB a katin guda ɗaya a kan ƙarfin wutar 350 W. Zaɓi template na PyTorch, vLLM ko Unsloth, tabbatar da tsarin H100 PCIE kai tsaye sannan ka haɗa ta SSH.

Yi hayar H100 PCIE Duk GPUs

Bayanan fasaha na H100 PCIE

VRAM a kowace GPU

80 GB

Ginin fasaha

NVIDIA Hopper

Ikon lissafi (Compute capability)

Lissafin FP32

≈ 41 TFLOPS

Gudun ƙwaƙwalwa (Bandwidth)

≈ 1760 GB/s

Ƙayyadaddun wutar lantarki

350 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 H100 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 H100 PCIE

Fine-tuning na samfuran 13B–34B

80 GB na ɗaukar LoRA a kan samfuran rukunin 30B a BF16 da QLoRA a kan samfuran rukunin 70B tare da Unsloth.

Gudanar da samfuran 70B da aka yi wa quantized

Kafa samfurin 4-bit 70B tare da vLLM ko SGLang a kan GPU guda ɗaya, domin ka guje wa raba aiki tsakanin GPUs da yawa (multi-GPU sharding) yayin gwaji.

Horarwa mai nau'in mixed-precision

Horar da samfuran transformers da diffusion tun daga tushe ko ci gaba da pre-training a kan Hopper mai compute capability 9.0.

Binciken samfuran bidiyo da hoto

Gudanar da manyan samfuran diffusion da ƙirƙirar bidiyo a ComfyUI waɗanda ke buƙatar ƙwaƙwalwa fiye da kowane katin na'ura na yau da kullum.

Shin H100 PCIE ita ce GPU da ta dace da aikinku?

Zaɓi H100 PCIE lokacin da ayyukanku ke buƙatar 80 GB na VRAM, memory bandwidth mai darajar datacenter, da kuma fasalullukan Hopper compute capability 9.0. Ga sauƙaƙan inference ko ƙananan samfura, workstation ko consumer GPU mai ƙarancin VRAM ya fi sauƙin kuɗi, yayin da buƙatun aiki mai ƙarfi sosai ka iya buƙatar nau'in datacenter mai tushen SXM.

H100 PCIE idan aka kwatanta da sauran cloud GPU

GPU	VRAM a kowace GPU	Lissafin FP32	Ƙayyadaddun wutar lantarki
NVIDIA H100 PCIE	80 GB	≈ 41 TFLOPS	350 W
NVIDIA H100 SXM	80 GB	≈ 53.5 TFLOPS	700 W	Cikakken bayani →
NVIDIA A800 PCIE	80 GB	≈ 15.6 TFLOPS	300 W	Cikakken bayani →
NVIDIA H100 NVL	94 GB	≈ 48.3 TFLOPS	400 W	Cikakken bayani →
NVIDIA CMP 170HX	64 GB	≈ 12.1 TFLOPS	250 W	Cikakken bayani →

Cloud GPU na H100 PCIE: tambayoyin da aka fi yi

Yi hayar cloud GPU na H100 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 H100 PCIE Duk GPUs