{"id":2147,"date":"2025-04-04T11:34:18","date_gmt":"2025-04-04T18:34:18","guid":{"rendered":"https:\/\/sycomp.com\/?p=2147"},"modified":"2025-05-20T06:53:03","modified_gmt":"2025-05-20T13:53:03","slug":"o-armazenamento-sycomp-otimiza-o-desempenho-da-gpu-ai","status":"publish","type":"post","link":"https:\/\/sycomp.com\/pt\/recurso\/o-armazenamento-sycomp-otimiza-o-desempenho-da-gpu-ai\/","title":{"rendered":"A plataforma de armazenamento inteligente de dados Sycomp otimiza o desempenho da GPU para 1,2 TB de taxa de transfer\u00eancia de E\/S para descoberta cient\u00edfica AI"},"content":{"rendered":"
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Enfrentando obst\u00e1culos significativos decorrentes de recursos insuficientes de GPU, esse setor
\nl\u00edder em desenvolvimento artificial intelligence (AI), buscou uma solu\u00e7\u00e3o para melhorar sua capacidade de inovar, escalar e competir em setores de mercado que dependem de computa\u00e7\u00e3o de alto desempenho (HPC), AI e aprendizado de m\u00e1quina (ML). <\/span><\/p>\n

A empresa precisava ter a capacidade de processar grandes tarefas AI no Google Cloud usando os n\u00f3s de GPU do Google para agilizar seus modelos de treinamento AI e infer\u00eancia, dando suporte a grandes modelos de linguagem e an\u00e1lise preditiva. Sem ampliar seu poder de computa\u00e7\u00e3o, a organiza\u00e7\u00e3o enfrentava um risco significativo para seu crescimento cont\u00ednuo e sucesso: <\/span><\/p>\n\n

    \n \t
  • Desenvolvimento de produtos<\/span><\/li>\n \t
  • Efici\u00eancia operacional <\/span><\/li>\n \t
  • Tempo de coloca\u00e7\u00e3o no mercado <\/span><\/li>\n \t
  • Experi\u00eancia do cliente <\/span><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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    Clique para fazer o download do estudo de caso.<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"

    Enfrentando obst\u00e1culos significativos decorrentes da insufici\u00eancia de recursos de GPU, esse l\u00edder do setor no desenvolvimento de artificial intelligence (AI) buscou uma solu\u00e7\u00e3o para melhorar sua capacidade de inovar, dimensionar e competir em setores de mercado que dependem de computa\u00e7\u00e3o de alto desempenho (HPC), AI e aprendizado de m\u00e1quina (ML). A empresa precisava ter a capacidade de processar grandes trabalhos AI no Google Cloud usando n\u00f3s de GPU do Google...<\/p>","protected":false},"author":3,"featured_media":2203,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","rs_blank_template":"","rs_page_bg_color":"","slide_template_v7":"","footnotes":""},"categories":[1],"tags":[],"resource-type":[13],"class_list":["post-2147","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","resource-type-case-study"],"acf":[],"yoast_head":"\nSycomp Intelligent Data Storage Platform Optimizes GPU Performance to 1.2 TB of IO Throughput for AI Scientific Discovery - Sycomp Inc<\/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:\/\/sycomp.com\/pt\/recurso\/o-armazenamento-sycomp-otimiza-o-desempenho-da-gpu-ai\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Sycomp Intelligent Data Storage Platform Optimizes GPU Performance to 1.2 TB of IO Throughput for AI Scientific Discovery\" \/>\n<meta property=\"og:description\" content=\"Facing significant obstacles arising from insufficient GPU resources, this industry leader in artificial intelligence (AI) development sought out a solution to improve their capability to innovate, scale and compete in market sectors that rely on high-performance computing (HPC), AI, and machine learning (ML). 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