** Ingantacciyar Aiwatar da Samfuran AI akan na'urorin Edge ta hanyar Haɗin Haɗin Kayan Kayan Aiki-Software ***

** Gabatarwa ***

Yaɗuwar na'urori na gefen ya haifar da sabbin dama don aikace-aikacen Intelligence Artificial (AI) da za a tura su a cikin ainihin lokaci, yana ba da damar aikace-aikace kamar gidaje masu kaifin baki, motoci masu cin gashin kansu, da sarrafa kansa na masana'antu. Koyaya, ƙayyadaddun albarkatun ƙididdigewa da ƙarancin ƙarfin na'urori na gefe suna haifar da ƙalubale masu mahimmanci ga jigilar ƙirar AI. A cikin wannan labarin, za mu bincika hanyar haɗin yanar gizo na AI, injiniyan software, da gine-gine don haɓaka aikin na'urar gaba, haɓaka ci gaban kwanan nan a ingantaccen ƙirar AI da dabarun ƙira na kayan masarufi.

** Kalubale na Aiwatar da Samfuran AI akan na'urorin Edge ***

Na'urorin Edge suna da ƙayyadaddun albarkatun lissafin su, gami da CPU, ƙwaƙwalwar ajiya, da amfani da wuta. Samfuran AI na al'ada, waɗanda galibi ana tsara su don tura tushen girgije, ba a inganta su don na'urorin gefen ba. A sakamakon haka, suna iya haifar da:

• ** Lalacewar ayyuka ***: Samfuran AI na iya yin aiki da kyau akan na'urorin gefuna, yana haifar da jinkirin lokacin amsawa da rage daidaito.
• ** Amfani da wutar lantarki ***: Samfuran AI na iya cinye babban ƙarfi, wanda zai iya zama damuwa ga na'urorin gefen baturi.
• ** Ƙuntataccen ƙwaƙwalwar ajiya ***: Samfuran AI na iya buƙatar adadin ƙwaƙwalwar ajiya mai yawa, wanda zai iya zama ƙalubale ga na'urori masu iyaka tare da ƙayyadaddun albarkatun ƙwaƙwalwar ajiya.

**Hanyoyin Haɗin-Hadware-Software Dabarun Zane ***

Don magance waɗannan ƙalubalen, dabarun ƙirar haɗin gwiwar hardware-software sun fito a matsayin mafita mai ban sha'awa. Waɗannan fasahohin sun haɗa da zayyana duka kayan aikin hardware da software na na'urar gefe a cikin tandem, inganta su don ƙaddamar da ƙirar AI.

###1. Samfurin Tsige

Gyaran samfuri ya ƙunshi cire ma'aunin nauyi da haɗin da ba dole ba daga samfurin AI, rage girmansa da buƙatun lissafi. Ana iya amfani da wannan fasaha zuwa duka hanyoyin sadarwa na jijiyoyi da bishiyoyi masu yanke shawara.

`` Python shigo da tocila shigo da tocila.nn kamar nn

ModelPruning (nn.Module): def init(kai): super (ModelPruning, kai).init() kai.fc1 = nn.Linear(784, 128) kai.fc2 = nn.Linear (128, 10)

def gaba (kai, x):
    x = torch.relu (self.fc1 (x))
    x = kai.fc2 (x)
    dawo x

model = ModelPruning() pruned_model = torch.nn.utils.prune_l1_unstructured (samfurin, 'nauyi', 0.1)

###*2. Fassarar Ilimi**

Distillation na ilimi ya haɗa da canja wurin ilimi daga babban, ƙirar AI mai rikitarwa zuwa ƙarami, mafi sauƙi. Ana iya amfani da wannan fasaha don rage girman da bukatun ƙididdiga na samfurin AI.

`` Python
shigo da tocila
shigo da tocila.nn kamar nn

Distillation Ilimin aji (nn.Module):
    def __init__(kai):
        super (KnowledgeDistillation, kai).__init__()
        kai.fc1 = nn.Linear(784, 128)
        kai.fc2 = nn.Linear (128, 10)

    def gaba (kai, x):
        x = torch.relu (self.fc1 (x))
        x = kai.fc2 (x)
        dawo x

malamin_model = ModelPruning()
student_model = Ilimi Distillation()

###3. Quantization

Ƙididdiga ya haɗa da rage madaidaicin ma'aunin AI da kunnawa, rage buƙatun ƙididdiga na ƙirar AI.

`` Python shigo da tocila shigo da tocila.nn kamar nn

Ƙididdigar aji (nn.Module): def init(kai): super(Quantization, self).init() kai.fc1 = nn.Linear(784, 128) kai.fc2 = nn.Linear (128, 10)

def gaba (kai, x):
    x = torch.relu (self.fc1 (x))
    x = kai.fc2 (x)
    dawo x

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

** Manyan Dokoki 5-10 da Akafi Amfani da su/Snippets**
------------------

| Umurni/Snippet | Bayani |
| --- | --- |
| `torch.nn.utils.prune_l1_unstructured(samfurin, 'nauyi', 0.1)` | Model pruning ta amfani da L1 normalization |
| `torch.quantization.quantize_dynamic(samfurin, {torch.nn.Linear}, dtype=torch.qint8)` | Ƙididdige ƙididdigewa ta amfani da ƙididdigewa mai ƙarfi |
| `torch.nn.utils.kldistance(malamin_model, dalibi_model)` | Distillation ilimi ta amfani da bambancin KL |
| `torch.nn.utils.weight_norm(model.fc1)` | Daidaita nauyi ta amfani da ka'idar nauyi |
| `torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0)` | Yanke gradient ta amfani da tsarin grad na al'ada |
| `torch.nn.utils.clip_grad_value_(model.parameters(), 1.0)` | Yanke gradient ta amfani da ƙimar grad clip |
| `torch.nn.utils.cire_nauyin_al'ada(model.fc1)` | Cire nauyin nauyi ta amfani da ka'idar cire nauyi |
| `torch.nn.utils.fuse_conv_bn_eval(model.fc1)` | Juyin juyi Layer fusion ta amfani da fuse conv bn eval |
| `torch.nn.utils.fuse_bn_eval(model.fc2)` | Batch normalization fusion ta amfani da fuse bn eval |
| `torch.nn.utils.fuse_bn_eval(model.fc1)` | Batch normalization fusion ta amfani da fuse bn eval |

**Kallon gani**
------------

``` jadawalin
{
  "type": "bar",
  "data": {
    "labels": ["Tsarin Samfura", "Knowledge Distillation", "Quantization"],
    "bayanin bayanai": {
      "label": "Daidaitacce",
      "bayanai": [0.9, 0.85, 0.8]
    }
  },
  "zaɓi": {
    "take": {
      "nuna": gaskiya,
      "text": "Daidaita Kwatancen"
    },
    "tatsuniya": {
      "nuni": gaskiya
    }
  }
}

Kammalawa

Ingantacciyar ƙirar ƙirar AI akan na'urorin gefen yana buƙatar haɗin kayan masarufi da dabarun ƙira na software. Gyaran samfuri, distillation na ilimi, da ƙididdigewa wasu fasahohin da za a iya amfani da su don rage girman da buƙatun ƙididdiga na ƙirar AI. Ta hanyar yin amfani da waɗannan fasahohin, masu haɓakawa za su iya ƙirƙirar samfuran AI waɗanda aka inganta don na'urori masu gefe, suna ba da damar aikace-aikacen lokaci-lokaci kamar gidaje masu wayo, motocin masu cin gashin kansu, da sarrafa kansa na masana'antu.

Aikin Gaba

Ayyukan gaba a wannan yanki sun haɗa da:

• ** Haɓaka sabbin fasahohin haɗin gwiwar kayan masarufi-software ***: Masu bincike da masu haɓakawa na iya bincika sabbin dabaru don haɓaka ƙirar AI don na'urorin gefen.
• ** Inganta ƙirar ƙirar ƙirar ƙira da algorithms distillation ilimi **: Haɓaka ingantaccen algorithms don ƙirar ƙirar ƙira da rarrabuwar ilimi na iya haifar da ingantaccen aiki da daidaito.
• Binciken amfani da wasu samfuran AI: Sauran samfuran AI, kamar bishiyar yanke shawara da dazuzzukan dazuzzuka, ana iya bincika don tura na'urar gefen.

Ta ci gaba da haɓaka fannin haɗin gwiwar hardware-software, za mu iya ƙirƙirar samfuran AI masu inganci da inganci don na'urori masu gefe, ba da damar aikace-aikace da yawa da lokuta masu amfani.