HN jira: Model Training Memory Simulator — Mun na GPU hakilijagabɔ bolodacogo nafa ka bon ka tɛmɛ fɔlɔ kan

GPU hakilijagabɔ wajibiyalenw jateminɛni sanni ka modɛli kalan boli daminɛ, o ye gɛlɛya dɔ ye min bɛ ye ka ban kosɛbɛ, nka a musaka ka bon masin kalanni baarakɛcogo la. Da wulilen kura dɔ Model Training Memory Simulator, n’o bɔra kɔsa in na Hacker News kan, o bɛ o gɛlɛya in ɲɛnabɔ kunkolo la, k’a to ɛntɛrinɛti ɲɛmɔgɔw ka VRAM baarakɛcogo fɔ, ka hakilijagabɔ gɛlɛyaw dɔn, ani ka kalanko labɛncogo ɲɛ — o bɛɛ kɛra sanni tensor kelen ka GPU gosi.

Modèle Training Memory Simulator ye mun ye ani mun na i ka kan k' i janto i la ?

Modèle kalan hakilijagabɔlan ye baarakɛminɛn ye min bɛ GPU hakilijagabɔ sennabɔli makɔnɔnen jate kalan jugu kalanni baara la ka da modeli jɔcogo kan, batch hakɛ, precision format, optimizer sugandili, ani parallelism strategy. Sani u ka sankaba misali sɔngɔ gɛlɛnw lamini dɔrɔn walasa ka CUDA Out of Memory fili siranninw sɔrɔ miniti damadɔ kalan kɔnɔ, ɛntɛrinɛti injiniyɛriw bɛ se ka kɔn ka hakilijagabɔ kɛcogo bɛɛ ladege.

Show HN porozɛ bɛ da wulilen fɛɛrɛ ta nin gɛlɛya in na, ka fɛɛrɛ wɛrɛ di min bɛ kɛnɛya, min bɛ sigidamɔgɔw ɲɛminɛ, ka tɛmɛn profilɛri baarakɛminɛnw kan minnu bɛ kɛ mɔgɔ yɛrɛ ta ye. A bɛ jatebla Kɛ paramɛtɛrɛw, 'gradients (yɔrɔ-yɔrɔ-yɔrɔ-yɔrɔw), 'optimiser (optimiser) cogoyaw, activations (baarakɛcogo) ani framework overhead (kalansenw) kan — o ye dɛmɛba duuru ye GPU hakilijagabɔ la kalan waati. Ekipu minnu bɛ baara caman kɛ NVIDIA A100w, H100w, walima hali RTX kartiw kan minnu bɛ se ka kɛ musakabɔlaw ye, nin labɛn sugu min bɛ kɛ ka kɔn o ɲɛ, o bɛ se ka dɔrɔmɛ ba caman bɔ jatebɔ tiɲɛnenw na ani lɛrɛ caman kɛli la.

GPU hakilijagabɔ bɛ ban cogo di modɛli kalanni senfɛ ?

Hakilila bɛ taa yɔrɔ min na kalan waati la, o faamuyali nafa ka bon kosɛbɛ ML injiniyɛri bɛɛ bolo. Simulatɛri bɛ musakabɔ tila ka kɛ kulu danfaralenw ye, minnu bɛ se ka fɔ ka ɲɛ:

• Modèle Paramètres : Senfagabana girinya raw . 7B-paramɛtiri modɛli min bɛ FP32 kɔnɔ, o bɛ 28 GB ɲɔgɔn ta girinya dɔrɔn na, a bɛ jigin ka se 14 GB ma FP16 walima BF16 kɔnɔ.
• Gradients : U maralen don kɔkanna jɛnsɛnni waati la , gradients bɛ paramɛtiriw yɛrɛ hakilijagabɔ senna-taama jira cogoya la .
• Optimizer States : Adama ni AdamW bɛ cogoya tensor fila wɛrɛw mara paramɛtiri kelen na (waati fɔlɔ ni filanan), o bɛ paramɛtiri hakilijagabɔ sabati cogo ɲuman na ni u bɛ baara kɛ ni FP32 optimiser cogoyaw ye.
• walew : cɛmancɛ bɔlenw maralen kɔfɛ tɛmɛsira kama . Olu bɛ sɛgɛsɛgɛli kɛ ni batɛmu hakɛ ni ɲɔgɔndan janya ye, o b’a to u bɛ fɛn caman sɛmɛntiya — wa a ka c’a la, u ka bon kosɛbɛ — hakilijagabɔla.
• Kalansenw kuntaalajan : CUDA sigida , hakilijagabɔ tilacogo , kumaɲɔgɔnya bufaw kalan tilatilali kama , ani waati kuntaala surun tilali minnu fɔli ka gɛlɛn ni simulatigɛ tɛ .

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Hakilila kunbaba : Kanko misali kalan boliba fanba la, optimiser cogoyaw ni baarakɛcogo — modeli girinya yɛrɛ tɛ — olu de ye hakilijagabɔlaw fangamaw ye. Hakilila-simulatɛri bɛ o tiɲɛni in jira sani i k’i yɛrɛ bila fɛnɲɛnamafagalan sɔngɔ gɛlɛnw na, ka jateminɛ kɛ ɛntɛrinɛti kan.

Mun b' a to nin Simulasi dafalen in bɛ bɔ baarakɛminɛn kɔrɔw la ?

Hacker News jɛkulu ye nin porozɛ in jaabi bawo a bɛ dimi lakikaw ɲɛnabɔ , fura minnu bɛ yen , olu bɛ to u ma ɲɛnabɔ . Sankaba dilanbaga fanba bɛ GPU hakilijagabɔlan jɔnjɔnw di, nka u man teli ka jatebɔ kɛ kalan kɛcogo ɲagaminenw na, gradient checkpointing, tensor parallelism, walima ZeRO-stage optimizations ka bɔ frameworks kɔnɔ i n’a fɔ DeepSpeed ani FSDP.

Nin simulator in bɛ o cogoya kɔrɔw misali di k'a jɛya . Ɛntɛrinɛti ɲɛmɔgɔw bɛ se k’u ka sigicogo kɛrɛnkɛrɛnnen don — a fɔ, 13B modɛli ni ZeRO Stage 3, gradient checkpointing bɛ se ka kɛ, BF16 mixed precision, ani micro-batch hakɛ 4 GPU 8 kɔnɔ — ka hakilijagabɔ tiɲɛni caman sɔrɔ minɛn kelen-kelen bɛɛ kɔnɔ. O kɛrɛnkɛrɛnnenya hakɛ de bɛ bolodaminɛn nafama dɔ faranfasi ka bɔ jateminɛ kɔfɛ.

dafalen cogoya fana kɔrɔ ye ko sigida bɛ se k' a janya . Laadalata architectures, optimizer implementations kura, ani hardware profiles bɔlenw bɛɛ bɛ se ka dɛmɛ ka segin, ka baarakɛminɛn in to a cogo la ni ML landscape bɛ ka wuli ni breakneck speed ye.

Jagokɛlaw bɛ se ka nafa sɔrɔ cogo di fɛnsɔrɔsiraw labɛnni hakilitigi la ?

K’a sɔrɔ simulator in jɔra ML injiniyɛriw kama , a nɔfɛkow bɛ taa jɛkulu o jɛkulu ma min bɛ wari bila AI sekow la . GPU misaliw labɛnni kojugu k’a sababu kɛ hakilijagabɔ wajibiyalenw ye minnu tɛ sigiyɔrɔ sɔrɔ, o bɛ sankaba wariw bonya. Labɛnbaliya bɛ na ni kalan boliw dɛsɛ ye, ka ɛntɛrinɛti lɛrɛ tiɲɛ, ani ka modɛli bilali kɔfɛ.

Jagokɛlaw minnu bɛ ka bonya minnu bɛ baarakɛcogo caman ɲɛnabɔ — k’a ta porozɛw ɲɛnabɔli la ka se wariko bolodacogo ma ka se kiliyanw ka sɛgɛsɛgɛli ma — sariyasen ye kelen ye : ka simulatigɛ sani i ka nafolo bila I mana GPU kuluw labɛn wo, walima i mana jago modulu minnu sugandi i ka kan ka baara kɛ i ka kulu ye, ka nafolo wajibiyalenw ja jɛlen sɔrɔ sani i ka sɛgɛsɛgɛli kɛ, o bɛ tiɲɛni bali ani ka sɔrɔw teliya.

O ye hakilina kelen ye min bɛ kɛnɛbaw kɔfɛ i n’a fɔ Mewayz, min bɛ jagokɛminɛn 207 di minnu bɛ ɲɔgɔn kan walasa ekipuw ka se k’u ka baarakɛcogo boloda, k’u ladege, k’u bonya k’a sɔrɔ u ma u yɛrɛ bila baarakɛminɛn tilalenw na kojugu. Hakilina min ye ka nafolo magow ladege sani u ka bila sen kan, o bɛ tali kɛ jago baarakɛcogo la kosɛbɛ i n’a fɔ a bɛ tali kɛ kalan misali la cogo min na.

Ɲininkali minnu bɛ kɛ tuma caman na

yala hakilijagabɔlan bɛ se ka hakilijagabɔ kɔfɛ filiw bali pewu degeliw senfɛ wa ?

Simulatɛri bɛ farati dɔgɔya kosɛbɛ ni jateminɛ tigitigiw dili ye ka da i ka labɛncogo kan, nka a tɛ se ka jatebɔ kɛ boli waati fɛn caman sɛgɛsɛgɛli bɛɛ la. Jateblaw jatebɔlanw fangama, donnakow janya caman ɲɔgɔnna, ani mɔgɔ sabananw ka gafemarayɔrɔ hakilijagabɔw bɛ se ka kɛ sababu ye ka fɛnw don minnu tɛ se ka fɔ ka ɲɛ. Simulatɛri bɔli minɛ i n’a fɔ bolodacogo min bɛ se ka da a kan — bujuru kɛ 10-15% kunkolo yɔrɔ wɛrɛ la ka ɲɛsin sɛnɛko kalan boliw ma walasa ka jatebɔ kɛ boli waati caman ɲɔgɔnnabɔli kan.

Yala nin simulator in nafa ka bon sɛgɛsɛgɛli ɲuman na wa walima boli dafalenw dɔrɔn de bɛ kɛ ka kɔn degeliw ɲɛ wa ?

A nafa ka bon kosɛbɛ u fila bɛɛ la . Fɛnɲɛnɛma-ko-ɲɛnabɔli ni fɛɛrɛw ye i n’a fɔ LoRA walima QLoRA bɛ hakilijagabɔ-cogo caman Changé bawo paramètres (daɲɛw) tilayɔrɔba dɔrɔn de bɛ gradients (gradients) ni optimiser states (yɔrɔw) de wajibiya. Simulatɛri ɲuman b’a to i bɛ nin paramɛtiri-fɛɛrɛw misali kɛ k’a jɛya, k’i dɛmɛ k’a dɔn ni sɛgɛsɛgɛli ɲuman baara bɛ bɛn musakabɔ GPU kelen ma walima ni a bɛ GPU caman infrastructure de wajibiya.

o bɛ tali kɛ cogo di musakaw ɲɛnabɔli la jagokɛminɛnw ni SaaS abonnés bɛɛ kɔnɔ ?

Sariyasen jɔnjɔn — ka nafolo tilacogo simulatigɛ ani k’a boloda ka sɔrɔ ka musaka kɛ — o bɛ tali kɛ diɲɛ fan bɛɛ la. I n’a fɔ ML ekipuw bɛ ba caman tiɲɛ GPUw la minnu ka ca kojugu, jagokɛlaw ka jɛkuluw bɛ ba caman tiɲɛ SaaS abonnés (abonnements) minnu bɛ ɲɔgɔn kan ani baarakɛminɛnw cakɛda tilalenw na. Ka i ka baarakɛminɛnw sigi senkan ka kɛ kɛnɛ kelen ye ni modulari baarakɛcogo ye, Mewayz bɛ jago baarakɛminɛnw gɛrɛ cogo min na n’a ka OS modulu 207 ye, o bɛ nafa sɔrɔli jira i ka GPU hakilijagabɔ tilali hakɛ bɛnnen na sani kalan ka daminɛ.

I labɛnnen don ka nafolomafɛnw ɲɛnabɔcogo hakilina kelen in kɛ i ka jago baarakɛcogo la wa ? Mewayz bɛ se di ekipu 138.000+ ma u mago bɛ modulu minnu na dɔrɔn, k’a daminɛ $19/mo la — fɛnw dicogo tɛmɛnen tɛ, tiɲɛni tɛ kɛ. aw ka kɔrɔbɔli fu daminɛ app.mewayz.com ani ka baarakɛjɛkulu tigitigi jɔ i ka kulu bɛ min ɲini .