Tsamaiso e nepahetseng ea Moetso oa AI ho Lisebelisoa tsa Edge ka Hardware-Software Co-Design

Selelekela

Keketseho ea lisebelisoa tse haufi e thehile menyetla e mecha ea hore lits'ebetso tsa Artificial Intelligence (AI) li kenngoe ka nako ea nnete, ho nolofalletsa lits'ebetso tse joalo ka matlo a bohlale, likoloi tse ikemetseng le li-automation tsa indasteri. Leha ho le joalo, lisebelisoa tse fokolang tsa computational le lithibelo tsa matla tsa lisebelisoa tse bohale li baka mathata a bohlokoa bakeng sa phepelo ea mohlala oa AI. Sengoliloeng sena, re tla hlahloba mateano a AI, boenjiniere ba software, le meralo ea ho ntlafatsa ts'ebetso ea sesebelisoa se matla, re matlafatsa tsoelo-pele ea morao-rao ea katleho ea mohlala oa AI le mekhoa ea co-design ea hardware.

**Mathata a Phepelo ea Mohlala oa AI ho Lisebelisoa tsa Edge **

Lisebelisoa tsa Edge li khetholloa ka lisebelisoa tsa bona tse fokolang tsa computational, ho kenyelletsa le CPU, memori le tšebeliso ea matla. Mefuta ea setso ea AI, eo hangata e etselitsoeng ho romelloa ka maru, ha e lokisetsoe lisebelisoa tse matla. Ka lebaka leo, li ka lebisa ho:

• Ho nyenyefala ha tshebetso: Mefuta ya AI e kanna ya se sebetse hantle disebedisweng tsa moraorao, e leng se lebisang ho nako ya ho araba butle le phokotso ya ho nepahala.
• Tšebeliso ea matla: Mefuta ea AI e ka sebelisa matla a bohlokoa, e leng ntho e ka tšoenyang lisebelisoa tse tsamaeang ka betri.
• Mathata a memori: Mefuta ea AI e ka hloka mohopolo o mongata, e ka bang phephetso bakeng sa lisebelisoa tse nang le lisebelisoa tse fokolang tsa mohopolo.

Mahlale a Moqapi oa Hardware-Software Co-Design

Ho rarolla liphephetso tsena, mekhoa ea boqapi ba software-software e hlahile e le tharollo e tšepisang. Mekhoa ena e kenyelletsa ho rala likarolo tsa Hardware le software tsa sesebelisoa sa bohale ka tandem, ho li ntlafatsa bakeng sa phepelo ea mohlala oa AI.

1. Mohlala oa ho Pruning

Ho faola mohlala ho kenyelletsa ho tlosa boima bo sa hlokahaleng le likhokahano ho mofuta oa AI, ho fokotsa boholo ba eona le litlhoko tsa computational. Mokhoa ona o ka sebelisoa ho marang-rang a neural le lifate tsa liqeto.

kenya lebone
import torch.nn joalo ka nn

class ModelPruning(nn.Module):
    def __init__(bowena):
        super(ModelPruning, self).__init__()
        self.fc1 = nn.Linear(784, 128)
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = torch.relu(self.fc1(x))
        x = self.fc2(x)
        khutla x

mohlala = ModelPruning()
pruned_model = torch.nn.utils.prune_l1_unstructured(mohlala, 'boima', 0.1)

2. Tsebo Distillation

Ho hlapolla tsebo ho kenyelletsa ho fetisetsa tsebo ho tloha mofuteng o moholo, o rarahaneng oa AI ho ea ho o monyenyane, o bonolo. Mokhoa ona o ka sebelisoa ho fokotsa boholo le litlhoko tsa computational tsa mohlala oa AI.

kenya lebone
import torch.nn joalo ka nn

Klase ea TseboDistillation(nn.Module):
    def __init__(bowena):
        super(KnowledgeDistillation, self).__init__()
        self.fc1 = nn.Linear(784, 128)
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = torch.relu(self.fc1(x))
        x = self.fc2(x)
        khutla x

teacher_model = ModelPruning()
student_model = KnowledgeDistillation()

**3. Quantization **

Quantization e kenyelletsa ho fokotsa ho nepahala ha boima ba mohlala oa AI le ts'ebetso, ho fokotsa litlhoko tsa khomphutha tsa mofuta oa AI.

kenya lebone
import torch.nn joalo ka nn

class Quantization(nn.Module):
    def __init__(bowena):
        super(Quantization, self).__init__()
        self.fc1 = nn.Linear(784, 128)
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = torch.relu(self.fc1(x))
        x = self.fc2(x)
        khutla x

mohlala = ModelPruning()
quantized_model = torch.quantization.quantize_dynamic(mohlala, {torch.nn.Linear}, dtype=torch.qint8)

Top 5-10 Litaelo/Lipotlana tse Sebelisitsoeng ka ho Fetisisa

Pono ya pono

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  "data": {
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    "lintlha tsa boitsebiso": {
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      "data": [0.9, 0.85, 0.8]
    }
  },
  "likgetho": {
    "sehlooho": {
      "bontša": 'nete,
      "text": "Papiso e Nepahetseng"
    },
    "tšōmo": {
      "pontšo": 'nete
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  }
}

Qetello

Tšebeliso e nepahetseng ea mohlala oa AI ho lisebelisoa tse ka morao e hloka motsoako oa lisebelisoa tsa hardware le software co-design. Ho faola mohlala, ho hlapolla tsebo, le quantization ke tse ling tsa mekhoa e ka sebelisoang ho fokotsa boholo le litlhoko tsa computational tsa mefuta ea AI. Ka ho sebelisa mekhoa ena, bahlahisi ba ka theha mefuta ea AI e ntlafalitsoeng bakeng sa lisebelisoa tse haufi, e nolofalletsang lits'ebetso tsa nako ea nnete joalo ka matlo a bohlale, likoloi tse ikemetseng le li-automation tsa indasteri.

Mosebetsi o Tlang

Mosebetsi oa nakong e tlang sebakeng sena o kenyelletsa:

• **Ho nts'etsapele mekhoa e mecha ea ho etsa li-hardware-software co-design **: Bafuputsi le bahlahisi ba ka hlahloba mekhoa e mecha ea ho ntlafatsa mefuta ea AI bakeng sa lisebelisoa tsa bohale.
• **Ho ntlafatsa mokhoa oa ho faola limela le li-algorithms tsa "distillation" tsa tsebo **: Ho ntlafala ha li-algorithms tse sebetsang hantle bakeng sa ho faola limela le ho hlahisa tsebo ho ka lebisa ts'ebetsong e ntle le ho nepahala.
• Ho etsa lipatlisiso ka tšebeliso ea mefuta e meng ea AI: Mefuta e meng ea AI, joalo ka lifate tsa liqeto le meru e sa reroang, e ka hlahlojoa bakeng sa phepelo ea lisebelisoa.

Ka ho tsoela pele ho ntšetsa pele tšimo ea hardware-software co-design, re ka theha mefuta e mengata ea AI e sebetsang hantle le e sebetsang bakeng sa lisebelisoa tsa bohale, e leng ho nolofalletsang mefuta e mengata ea likopo le linyeoe tsa tšebeliso.