Shin A800 PCIE za ta iya gudanar da samfurin 70B?

Ƙwarai, idan aka yi mata quantized. Nauyin 70B yana ɗaukar kusan 35–40 GB a 4-bit, don haka yana shiga cikin 80 GB tare da sauran sarari don context. Gudanar da 70B a 16-bit yana buƙatar kimanin 140 GB, wanda hakan ke nuna buƙatar H200 NVL.

Ta yaya A800 PCIE ta bambanta da A100 PCIE?

Tsarinsu ɗaya ne na zuri'ar Ampere da kuma 15.6 TFLOPS FP32, amma an bayyana A800 PCIE da 80 GB maimakon 40 GB da kuma 1598 GB/s maimakon 1313 GB/s, saboda haka tana ɗaukar manyan samfura kuma tana gudanar da su cikin ɗan sauri.

Shin ya kamata in zaɓi A800 PCIE ko H100 PCIE?

Dukansu suna da 80 GB. H100 PCIE mai tsarin Hopper tana ƙara 41 TFLOPS FP32 da 1760 GB/s, don haka ta fi sauri a kowace sa'ar aiki; A800 PCIE ta fi dacewa idan farashin yanzu ya fi sauƙi kuma gudun Ampere ya isa.

Waɗanne templates ne ke aiki a kan A800 PCIE?

Templates na PyTorch, vLLM, SGLang, Ollama, Unsloth da ComfyUI suna lissafa ƙarancin nau'in CUDA da VRAM da suke buƙata; allon sarrafawa na Cloudj yana ba da templates ɗin da GPU za ta iya gudanarwa ne kawai.

GPU Cloud · NVIDIA · Ampere

Yi hayar NVIDIA A800 PCIE GPU mai 80 GB VRAM

Yi hayar A800 PCIE GPUs a kan kowace sa'a a Cloudj: 80 GB VRAM a kan NVIDIA Ampere tare da kimanin 1598 GB/s na memory bandwidth, ta yadda manyan samfuran LLMs na rukunin 70B za su iya shiga a kan kati guda. An tsara shi ne domin ƙungiyoyin AI da ke buƙatar ninki biyu na ƙwaƙwalwar A100 40 GB domin serving, fine-tuning da ayyukan long-context, tare da 15.6 TFLOPS FP32 da iyakar wutar 300 W. Fara aiki daga samfurin vLLM, SGLang ko Unsloth kuma ka haɗu ta hanyar SSH.

Yi hayar A800 PCIE Duk GPUs

Bayanan fasaha na A800 PCIE

VRAM a kowace GPU

80 GB

Ginin fasaha

NVIDIA Ampere

Ikon lissafi (Compute capability)

Lissafin FP32

≈ 15.6 TFLOPS

Gudun ƙwaƙwalwa (Bandwidth)

≈ 1598 GB/s

Ƙayyadaddun wutar lantarki

300 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 A800 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 A800 PCIE

Samfuran 70B a kan GPU guda

Gudanar da samfurin 70B na 4-bit tare da sauran sarari don KV cache, ko samfurin 30B–34B a 16-bit, ta amfani da vLLM ko SGLang.

Ayyukan inference na long-context

80 GB tana ba da sarari don dogayen prompts da jerin ayyuka da yawa a lokaci ɗaya waɗanda za su cika katin 40 GB.

Fine-tuning ga matsakaitan LLMs

Gudanar da LoRA a kan samfuran 13B–34B a BF16 ko QLoRA a kan manyan samfura tare da Unsloth, ba tare da raba aiki a tsakanin GPUs ba.

Aikin data science mai buƙatar ƙwaƙwalwa mai yawa

Adana manyan tensors, graphs ko feature matrices a cikin ƙwaƙwalwar GPU domin ayyukan RAPIDS ko PyTorch.

Shin A800 PCIE ita ce GPU da ta dace da aikinku?

Zaɓi A800 PCIE idan babban abin da kake buƙata shi ne ƙarfin ƙwaƙwalwa na 80 GB don manyan samfuran AI maimakon ƙarfin lissafin single-precision kawai. Idan aikinka yana iya shiga ƙaramar ƙwaƙwalwa, workstation ko GPU ta yau da kullun mai ƙarancin VRAM ta fi dacewa, yayin da ayyukan da ke buƙatar ƙarfin lissafi sosai za su fi cin gajiyar sabbin tsarukan datacenter na zamani.

A800 PCIE idan aka kwatanta da sauran cloud GPU

GPU	VRAM a kowace GPU	Lissafin FP32	Ƙayyadaddun wutar lantarki
NVIDIA A800 PCIE	80 GB	≈ 15.6 TFLOPS	300 W
NVIDIA H100 PCIE	80 GB	≈ 41 TFLOPS	350 W	Cikakken bayani →
NVIDIA H100 SXM	80 GB	≈ 53.5 TFLOPS	700 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 A800 PCIE: tambayoyin da aka fi yi

Yi hayar cloud GPU na A800 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 A800 PCIE Duk GPUs