{"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":"el-almacenamiento-sycomp-optimiza-el-rendimiento-de-la-gpu-ai","status":"publish","type":"post","link":"https:\/\/sycomp.com\/es\/resource\/sycomp-storage-optimizes-gpu-performance-ai\/","title":{"rendered":"La plataforma de almacenamiento inteligente de datos Sycomp optimiza el rendimiento de la GPU hasta alcanzar 1,2 TB de rendimiento de E\/S para el descubrimiento cient\u00edfico AI"},"content":{"rendered":"
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Esta industria se enfrenta a importantes obst\u00e1culos derivados de la insuficiencia de recursos de la GPU.
\nl\u00edder en desarrollo artificial intelligence (AI) buscaba una soluci\u00f3n para mejorar su capacidad de innovar, escalar y competir en sectores del mercado que dependen de la inform\u00e1tica de alto rendimiento (HPC), AI y el aprendizaje autom\u00e1tico (ML). <\/span><\/p>\n

La empresa necesitaba la capacidad de procesar grandes trabajos AI en Google Cloud utilizando los nodos de GPU de Google para agilizar sus modelos de formaci\u00f3n e inferencia AI, respaldando grandes modelos ling\u00fc\u00edsticos y an\u00e1lisis predictivos. Sin ampliar su potencia de c\u00e1lculo, la organizaci\u00f3n se enfrentaba a un riesgo significativo para su crecimiento y \u00e9xito continuados en: <\/span><\/p>\n\n

    \n \t
  • Desarrollo de productos<\/span><\/li>\n \t
  • Eficacia operativa <\/span><\/li>\n \t
  • Plazo de comercializaci\u00f3n <\/span><\/li>\n \t
  • Experiencia del 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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    Haga clic para descargar el estudio 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":"

    Enfrentada a importantes obst\u00e1culos derivados de la insuficiencia de recursos de GPU, esta empresa l\u00edder en el desarrollo de artificial intelligence (AI) busc\u00f3 una soluci\u00f3n para mejorar su capacidad de innovar, escalar y competir en sectores del mercado que dependen de la computaci\u00f3n de alto rendimiento (HPC), AI y el aprendizaje autom\u00e1tico (ML). La empresa necesitaba la capacidad de procesar grandes trabajos AI en Google Cloud utilizando nodos GPU de 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\/es\/recurso\/el-almacenamiento-sycomp-optimiza-el-rendimiento-de-la-gpu-ai\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\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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