{"id":490,"date":"2025-12-09T20:01:27","date_gmt":"2025-12-09T17:01:27","guid":{"rendered":"https:\/\/neku.ai\/throughput-nedir-ai-performans\/"},"modified":"2025-12-09T20:01:59","modified_gmt":"2025-12-09T17:01:59","slug":"throughput-nedir-ai-performans","status":"publish","type":"post","link":"https:\/\/neku.ai\/en\/throughput-nedir-ai-performans\/","title":{"rendered":"Throughput kavrami ile yapay zeka performansini optimize etme"},"content":{"rendered":"

Throughput nedir<\/strong><\/h1>\n
\n

Giri\u015f<\/strong><\/h3>\n

Throughput, bir sistemin belirli bir zaman diliminde i\u015fleyebildi\u011fi veri veya i\u015flem miktar\u0131n\u0131 ifade eder. Yapay zeka, LLM modelleri ve otomasyon sistemlerinde throughput, performans\u0131n en kritik g\u00f6stergelerinden biridir. Temel AI kavramlar\u0131 aras\u0131nda yer alan throughput, bir modelin veya yaz\u0131l\u0131m\u0131n h\u0131z\u0131n\u0131, \u00f6l\u00e7eklenebilirli\u011fini ve verimlili\u011fini do\u011frudan etkiler.<\/p>\n

\n

Throughput nedir tan\u0131m\u0131<\/strong><\/h3>\n

Throughput, bir sistemin \u00fcretim veya i\u015flem hatt\u0131nda birim zamanda tamamlad\u0131\u011f\u0131 i\u015f miktar\u0131d\u0131r. Yaz\u0131l\u0131m, donan\u0131m veya makine \u00f6\u011frenimi sistemlerinde bu, saniye ba\u015f\u0131na i\u015flenen istek, hesaplama ya da veri miktar\u0131 ile \u00f6l\u00e7\u00fcl\u00fcr. Y\u00fcksek throughput, sistemin daha fazla i\u015fi ayn\u0131 s\u00fcrede tamamlayabildi\u011fini g\u00f6sterir ve bu da kullan\u0131c\u0131 deneyimi ile kaynak verimlili\u011fini art\u0131r\u0131r.<\/p>\n

\n

throughput nas\u0131l \u00e7al\u0131\u015f\u0131r<\/strong><\/h3>\n

Bir sistemin throughput de\u011feri; donan\u0131m \u00f6zellikleri, a\u011f bant geni\u015fli\u011fi, algoritma verimlili\u011fi ve paralel i\u015flem kapasitesine g\u00f6re \u015fekillenir. \u00d6rne\u011fin bir LLM modelinde, GPU \u00e7ekirdek say\u0131s\u0131 ve modelin batch size parametresi throughput \u00fczerinde do\u011frudan etkilidir.<\/p>\n

Temel parametreler ve ayarlar<\/strong><\/h4>\n
    \n
  • Batch size:<\/strong> Ayn\u0131 anda i\u015flenen veri \u00f6rne\u011fi say\u0131s\u0131 throughput’u etkiler. <\/li>\n
  • Concurrency:<\/strong> Paralel i\u015flem say\u0131s\u0131 artt\u0131k\u00e7a throughput y\u00fckselir ancak kaynak kullan\u0131m\u0131 da artar. <\/li>\n
  • Latency:<\/strong> D\u00fc\u015f\u00fck gecikme s\u00fcreleri throughput\u2019un s\u00fcrd\u00fcr\u00fclebilirli\u011fini sa\u011flar. <\/li>\n
  • Pipeline yap\u0131s\u0131:<\/strong> Veri ak\u0131\u015f\u0131 optimize edilmediyse throughput s\u0131n\u0131rlan\u0131r.<\/li>\n<\/ul>\n

    S\u0131k yap\u0131lan hatalar ve ka\u00e7\u0131nma y\u00f6ntemleri<\/strong><\/h4>\n
      \n
    • Fazla b\u00fcy\u00fck batch size se\u00e7mek, bellek ta\u015fmas\u0131na yol a\u00e7abilir. <\/li>\n
    • A\u015f\u0131r\u0131 concurrency ayar\u0131 sistemde t\u0131kan\u0131kl\u0131k yaratabilir. <\/li>\n
    • \u00d6l\u00e7\u00fcm yap\u0131lmadan parametre de\u011fi\u015fikli\u011fi performans\u0131 olumsuz etkileyebilir.
      \nBu hatalardan ka\u00e7\u0131nmak i\u00e7in her de\u011fi\u015fiklik sonras\u0131 \u00f6l\u00e7\u00fcm yap\u0131lmal\u0131 ve veri ak\u0131\u015f\u0131 izlenmelidir.<\/li>\n<\/ul>\n

      Ger\u00e7ek sistemlerde uygulama \u00f6rnekleri<\/strong><\/h4>\n

      Bir \u00fcretim hatt\u0131nda saniyede 100 birim \u00e7\u0131kt\u0131 almak hedefleniyorsa; sens\u00f6rler, kuyruk sistemi ve i\u015flemci kapasitesi buna uygun yap\u0131land\u0131r\u0131l\u0131r. Benzer \u015fekilde, bir yapay zeka API servisi saniyede 1000 iste\u011fi i\u015fleyebiliyorsa, throughput de\u011feri bu performans\u0131 temsil eder.<\/p>\n

      \n

      Teknik a\u00e7\u0131klama (derin seviye)<\/strong><\/h3>\n

      Beginner seviyesinde throughput’u bir fabrika hatt\u0131 gibi d\u00fc\u015f\u00fcnebiliriz. Her istasyonda i\u015flenen \u00fcr\u00fcn say\u0131s\u0131, sistemin genel h\u0131z\u0131n\u0131 belirler. E\u011fer istasyonlardan biri yava\u015fsa, genel throughput s\u0131n\u0131rlan\u0131r.
      \nYapay zeka modelinde bu istasyonlar, veri \u00f6n i\u015fleme, model \u00e7al\u0131\u015ft\u0131rma ve \u00e7\u0131kt\u0131 \u00fcretme ad\u0131mlar\u0131n\u0131 temsil eder. Her ad\u0131m\u0131n optimize edilmesiyle genel throughput art\u0131r\u0131l\u0131r.<\/p>\n

      \n

      \u0130\u015fletmeler i\u00e7in neden kritiktir<\/strong><\/h3>\n
        \n
      • Performans:<\/strong> H\u0131zl\u0131 sistemler, kullan\u0131c\u0131ya an\u0131nda yan\u0131t verir. <\/li>\n
      • G\u00fcvenilirlik:<\/strong> Y\u00fck alt\u0131nda kararl\u0131 throughput, sistemin istikrarl\u0131 \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 g\u00f6sterir. <\/li>\n
      • Maliyet:<\/strong> Kaynaklar\u0131n verimli kullan\u0131m\u0131 hesaplama maliyetlerini d\u00fc\u015f\u00fcr\u00fcr. <\/li>\n
      • \u00d6l\u00e7ekleme:<\/strong> Artan kullan\u0131c\u0131 trafi\u011fine kar\u015f\u0131 esnek b\u00fcy\u00fcme sa\u011flar. <\/li>\n
      • Otomasyon:<\/strong> Y\u00fcksek throughput, i\u015f ak\u0131\u015flar\u0131n\u0131 h\u0131zland\u0131r\u0131r. <\/li>\n
      • Karar alma:<\/strong> Veri h\u0131zl\u0131 i\u015flendi\u011finde analitik karar s\u00fcre\u00e7leri iyile\u015fir. <\/li>\n
      • Operasyonel verimlilik:<\/strong> Departmanlar aras\u0131nda s\u00fcre\u00e7 b\u00fct\u00fcnl\u00fc\u011f\u00fc artar.<\/li>\n<\/ul>\n
        \n

        Bu kavram NeKu.AI i\u00e7inde nas\u0131l uygulan\u0131r<\/strong><\/h3>\n

        NeKu.AI, yapay zeka tabanl\u0131 s\u00fcre\u00e7 otomasyonlar\u0131nda throughput \u00f6l\u00e7\u00fcmlerini temel performans metri\u011fi olarak kullan\u0131r. \u00d6rne\u011fin n8n orkestrasyonlar\u0131nda, belirli bir i\u015f ak\u0131\u015f\u0131n\u0131n saniyede ka\u00e7 g\u00f6rev tamamlad\u0131\u011f\u0131 analiz edilerek darbo\u011fazlar tespit edilir. SAP entegrasyonlar\u0131nda ise API \u00e7a\u011fr\u0131lar\u0131 aras\u0131ndaki throughput, i\u015flem zincirinin stabilitesi i\u00e7in kritik fakt\u00f6rd\u00fcr. Bu yakla\u015f\u0131mla sistemler yaln\u0131zca do\u011fru \u00e7al\u0131\u015fmakla kalmaz, ayn\u0131 zamanda s\u00fcrd\u00fcr\u00fclebilir h\u0131zda i\u015flem \u00fcretir.<\/p>\n

        \n

        AI geli\u015ftiricileri, \u00fcr\u00fcn y\u00f6neticileri, SAP dan\u0131\u015fmanlar\u0131 i\u00e7in ger\u00e7ek bir senaryo<\/strong><\/h3>\n
          \n
        1. Sorun:<\/strong> Bir LLM tabanl\u0131 m\u00fc\u015fteri destek sistemi, artan istek y\u00fck\u00fc alt\u0131nda yava\u015f yan\u0131t veriyor. <\/li>\n
        2. Ba\u011flam:<\/strong> Model, SAP\u2019den veri \u00e7ekerek yan\u0131t olu\u015fturuyor ancak throughput de\u011feri s\u00fcrekli d\u00fc\u015f\u00fcyor. <\/li>\n
        3. Kavram\u0131n uygulanmas\u0131:<\/strong> Geli\u015ftirici ekip n8n \u00fczerinden paralel i\u015f ak\u0131\u015f\u0131 yap\u0131land\u0131r\u0131yor ve batch size parametresini optimize ediyor. <\/li>\n
        4. Sonu\u00e7:<\/strong> Saniyede i\u015flenen istek say\u0131s\u0131 iki kat\u0131na \u00e7\u0131k\u0131yor. <\/li>\n
        5. \u0130\u015f etkisi:<\/strong> Daha y\u00fcksek throughput ile ayn\u0131 kaynakla daha fazla kullan\u0131c\u0131 hizmet al\u0131yor ve i\u015flem maliyetleri azal\u0131yor.<\/li>\n<\/ol>\n
          \n

          S\u0131k yap\u0131lan hatalar ve en iyi uygulamalar<\/strong><\/h3>\n
            \n
          • \n

            Hatalar:<\/strong> <\/p>\n<\/li>\n

          • \n

            Throughput yerine yaln\u0131zca latency\u2019yi izlemek. <\/p>\n<\/li>\n

          • \n

            Donan\u0131m kaynaklar\u0131n\u0131 yanl\u0131\u015f \u00f6l\u00e7eklendirmek. <\/p>\n<\/li>\n

          • \n

            Kuyruk sistemlerini optimize etmemek. <\/p>\n<\/li>\n

          • \n

            En iyi uygulamalar:<\/strong> <\/p>\n<\/li>\n

          • \n

            \u00d6l\u00e7\u00fcm, izleme ve olay kay\u0131tlar\u0131n\u0131 s\u00fcrekli tutmak. <\/p>\n<\/li>\n

          • \n

            Parametre de\u011fi\u015fikliklerini kontroll\u00fc \u015fekilde test etmek. <\/p>\n<\/li>\n

          • \n

            n8n, Prometheus veya SAP Monitor ara\u00e7lar\u0131n\u0131 d\u00fczenli kullanmak. <\/p>\n<\/li>\n

          • \n

            Darbo\u011fazlar\u0131 model ve i\u015f ak\u0131\u015f\u0131 seviyesinde ele almak.<\/p>\n<\/li>\n<\/ul>\n

            \n

            Sonu\u00e7<\/strong><\/h3>\n

            Throughput, hem teknik performans\u0131n hem de i\u015fletme verimlili\u011finin somut g\u00f6stergesidir. Yapay zeka ve otomasyon sistemlerinde do\u011fru \u00f6l\u00e7\u00fcld\u00fc\u011f\u00fcnde, kaynak planlama ve kullan\u0131c\u0131 deneyimi do\u011frudan iyile\u015fir. NeKu.AI’nin temel kavram serisi i\u00e7inde throughput, her geli\u015ftirici ve dan\u0131\u015fman i\u00e7in sistem performans\u0131n\u0131n anla\u015f\u0131lmas\u0131 a\u00e7\u0131s\u0131ndan temel bir yap\u0131 ta\u015f\u0131d\u0131r.<\/p>","protected":false},"excerpt":{"rendered":"

            Throughput nedir Giri\u015f Throughput, bir sistemin belirli bir zaman diliminde i\u015fleyebildi\u011fi veri veya i\u015flem miktar\u0131n\u0131 ifade eder. Yapay zeka, LLM modelleri ve otomasyon sistemlerinde throughput, performans\u0131n [\u2026]<\/span><\/p>\n","protected":false},"author":2,"featured_media":491,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_sitemap_exclude":false,"_sitemap_priority":"","_sitemap_frequency":"","footnotes":""},"categories":[],"tags":[],"class_list":["post-490","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"yoast_head":"\nThroughput kavrami ile yapay zeka performansini optimize etme - NeKu.AI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/neku.ai\/en\/throughput-nedir-ai-performans\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Throughput kavrami ile yapay zeka performansini optimize etme - NeKu.AI\" \/>\n<meta property=\"og:description\" content=\"Throughput nedir Giri\u015f Throughput, bir sistemin belirli bir zaman diliminde i\u015fleyebildi\u011fi veri veya i\u015flem miktar\u0131n\u0131 ifade eder. 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