{"id":13838,"date":"2026-10-01T16:43:08","date_gmt":"2026-10-01T13:43:08","guid":{"rendered":"https:\/\/gtmteknoloji.com\/b2b\/?post_type=product&#038;p=13838"},"modified":"2026-10-01T16:43:08","modified_gmt":"2026-10-01T13:43:08","slug":"supermicro-srs-gb300-nvl72-nvidia-gb300-nvl72","status":"publish","type":"product","link":"https:\/\/gtmteknoloji.com\/b2b\/magaza\/gpu-server\/sivi-sogutmali-gpu-server\/supermicro-srs-gb300-nvl72-nvidia-gb300-nvl72\/","title":{"rendered":"Supermicro SRS-GB300-NVL72 NVIDIA GB300 NVL72 Rack-Scale AI Sistemi \u2013 72x B300 GPU"},"content":{"rendered":"<style>\n.gtm-product{\n  --green:#76B900;\n  --green-dark:#5d9200;\n  --green-hover:#edf7df;\n  --green-soft:#f5faee;\n  --border:#dfe5da;\n  --text:#252a22;\n  --muted:#5f6759;\n  max-width:980px;\n  margin:0 auto;\n  color:var(--text);\n  font-family:inherit;\n  line-height:1.65;\n}<\/p>\n<p>.gtm-product *{\n  box-sizing:border-box;\n}<\/p>\n<p>.gtm-product p{\n  margin:0 0 12px;\n}<\/p>\n<p>.gtm-product h2{\n  margin:26px 0 13px;\n  padding-left:12px;\n  border-left:4px solid var(--green);\n  color:var(--text);\n  font-size:22px;\n  line-height:1.3;\n}<\/p>\n<p>.gtm-intro{\n  padding:20px 22px;\n  background:#fff;\n  border:1px solid var(--border);\n  border-left:5px solid var(--green);\n  border-radius:11px;\n}<\/p>\n<p>.gtm-intro:hover{\n  background:var(--green-soft);\n  border-color:#bcd58e;\n}<\/p>\n<p>.gtm-grid{\n  display:grid;\n  grid-template-columns:repeat(4,1fr);\n  gap:10px;\n}<\/p>\n<p>.gtm-card{\n  position:relative;\n  overflow:hidden;\n  padding:16px;\n  background:#fff;\n  border:1px solid var(--border);\n  border-radius:9px;\n  transition:.18s ease;\n}<\/p>\n<p>.gtm-card:before{\n  content:\"\";\n  position:absolute;\n  left:0;\n  top:0;\n  width:4px;\n  height:100%;\n  background:var(--green);\n}<\/p>\n<p>.gtm-card:hover{\n  transform:translateY(-2px);\n  background:var(--green-hover);\n  border-color:#bcd58e;\n}<\/p>\n<p>.gtm-card strong{\n  display:block;\n  margin-bottom:4px;\n  color:var(--green-dark);\n  font-size:16px;\n  line-height:1.35;\n}<\/p>\n<p>.gtm-card span{\n  display:block;\n  color:var(--muted);\n  font-size:13px;\n  line-height:1.5;\n}<\/p>\n<p>.gtm-table-wrap{\n  overflow-x:auto;\n  border:1px solid var(--border);\n  border-radius:10px;\n  background:#fff;\n}<\/p>\n<p>.gtm-table{\n  width:100%;\n  min-width:720px;\n  margin:0;\n  border-collapse:collapse;\n  background:#fff;\n}<\/p>\n<p>.gtm-table th,\n.gtm-table td{\n  padding:12px 13px;\n  border-bottom:1px solid #e8ece5;\n  text-align:left;\n  vertical-align:top;\n  font-size:14px;\n}<\/p>\n<p>.gtm-table th{\n  width:18%;\n  background:#f5faee;\n  color:#30372d;\n  font-weight:700;\n}<\/p>\n<p>.gtm-table td{\n  width:32%;\n  background:#fff;\n  color:#41493d;\n}<\/p>\n<p>.gtm-table tr:hover th{\n  background:#f5faee;\n  color:#30372d;\n}<\/p>\n<p>.gtm-table tr:hover td{\n  background:#fff;\n  color:#41493d;\n}<\/p>\n<p>.gtm-table tr:last-child th,\n.gtm-table tr:last-child td{\n  border-bottom:none;\n}<\/p>\n<p>.gtm-info{\n  padding:17px 19px;\n  background:#fff;\n  border:1px solid var(--border);\n  border-left:4px solid var(--green);\n  border-radius:9px;\n}<\/p>\n<p>.gtm-info:hover{\n  background:var(--green-hover);\n  border-color:#bcd58e;\n}<\/p>\n<p>.gtm-faq{\n  display:grid;\n  gap:9px;\n}<\/p>\n<p>.gtm-faq details{\n  overflow:hidden;\n  background:#fff;\n  border:1px solid var(--border);\n  border-left:4px solid var(--green);\n  border-radius:9px;\n}<\/p>\n<p>.gtm-faq summary{\n  position:relative;\n  padding:15px 46px 15px 16px;\n  cursor:pointer;\n  list-style:none;\n  color:var(--text);\n  font-weight:700;\n  font-size:15px;\n}<\/p>\n<p>.gtm-faq summary::-webkit-details-marker{\n  display:none;\n}<\/p>\n<p>.gtm-faq summary:after{\n  content:\"+\";\n  position:absolute;\n  right:15px;\n  top:50%;\n  transform:translateY(-50%);\n  color:var(--green-dark);\n  font-size:21px;\n}<\/p>\n<p>.gtm-faq details[open] summary:after{\n  content:\"\u2212\";\n}<\/p>\n<p>.gtm-faq-answer{\n  padding:0 16px 15px;\n  color:#535c4d;\n  font-size:14px;\n}<\/p>\n<p>@media(max-width:800px){\n  .gtm-grid{\n    grid-template-columns:repeat(2,1fr);\n  }\n}<\/p>\n<p>@media(max-width:520px){\n  .gtm-grid{\n    grid-template-columns:1fr;\n  }<\/p>\n<p>  .gtm-product h2{\n    font-size:18px;\n  }<\/p>\n<p>  .gtm-intro{\n    padding:17px;\n  }\n}\n<\/style>\n<div class=\"gtm-product\">\n<div class=\"gtm-intro\">\n<p>Supermicro SRS-GB300-NVL72, s\u0131v\u0131 so\u011futmal\u0131 bir rack-scale AI \u00e7\u00f6z\u00fcm\u00fcd\u00fcr. Sistem, NVIDIA GB300 Grace Blackwell Ultra Superchip mimarisini kullan\u0131r. Ayr\u0131ca 72 adet NVIDIA B300 GPU ve 36 adet NVIDIA Grace CPU i\u00e7erir.<\/p>\n<p>Bunun yan\u0131nda GPU ba\u015f\u0131na 288 GB HBM3e bellek sunar. Rack seviyesinde 21 TB&#8217;a kadar HBM3e GPU belle\u011fi bulunur. Ayr\u0131ca sistem belle\u011fi 17 TB&#8217;a kadar LPDDR5X kapasitesine ula\u015f\u0131r. B\u00f6ylece sistem, y\u00fcksek kapasiteli bellek yap\u0131s\u0131n\u0131 tek rack \u00fczerinde bir araya getirir.<\/p>\n<\/div>\n<h2>Supermicro SRS-GB300-NVL72 \u00d6ne \u00c7\u0131kan \u00d6zellikleri<\/h2>\n<div class=\"gtm-grid\">\n<div class=\"gtm-card\">\n<strong>72x NVIDIA B300 GPU<\/strong><br \/>\n<span>NVIDIA GB300 Grace Blackwell Ultra Superchip<\/span>\n<\/div>\n<div class=\"gtm-card\">\n<strong>36x NVIDIA Grace CPU<\/strong><br \/>\n<span>Rack \u00f6l\u00e7e\u011finde b\u00fct\u00fcnle\u015fik i\u015flem altyap\u0131s\u0131<\/span>\n<\/div>\n<div class=\"gtm-card\">\n<strong>21 TB HBM3e<\/strong><br \/>\n<span>Rack seviyesinde GPU belle\u011fi<\/span>\n<\/div>\n<div class=\"gtm-card\">\n<strong>Direct Liquid Cooling<\/strong><br \/>\n<span>S\u0131v\u0131 so\u011futmal\u0131 rack-scale yap\u0131<\/span>\n<\/div>\n<\/div>\n<h2>Supermicro SRS-GB300-NVL72 Teknik \u00d6zellikleri<\/h2>\n<div class=\"gtm-table-wrap\">\n<table class=\"gtm-table\">\n<tbody>\n<tr>\n<th>Model<\/th>\n<td>SRS-GB300-NVL72<\/td>\n<th>Sistem Tipi<\/th>\n<td>Liquid Cooled Rack-Scale Solution<\/td>\n<\/tr>\n<tr>\n<th>GPU<\/th>\n<td>72x NVIDIA B300 GPU<\/td>\n<th>CPU<\/th>\n<td>36x NVIDIA Grace CPU<\/td>\n<\/tr>\n<tr>\n<th>GPU Mimarisi<\/th>\n<td>NVIDIA GB300 Grace Blackwell Ultra<\/td>\n<th>GPU Belle\u011fi<\/th>\n<td>21 TB&#8217;a kadar HBM3e<\/td>\n<\/tr>\n<tr>\n<th>GPU Ba\u015f\u0131na Bellek<\/th>\n<td>288 GB HBM3e<\/td>\n<th>Sistem Belle\u011fi<\/th>\n<td>17 TB&#8217;a kadar LPDDR5X<\/td>\n<\/tr>\n<tr>\n<th>Depolama<\/th>\n<td>144x E1.S PCIe 5.0 s\u00fcr\u00fcc\u00fc yuvas\u0131na kadar<\/td>\n<th>Compute Node<\/th>\n<td>18x 1U ARS-121GL-NB3<\/td>\n<\/tr>\n<tr>\n<th>NVLink Switch<\/th>\n<td>9x<\/td>\n<th>GPU Interconnect<\/th>\n<td>1.8 TB\/s<\/td>\n<\/tr>\n<tr>\n<th>Compute Fabric<\/th>\n<td>NVIDIA Quantum-X800 InfiniBand \/ Spectrum-X Ethernet<\/td>\n<th>A\u011f H\u0131z\u0131<\/th>\n<td>800 Gb\/s&#8217;ye kadar<\/td>\n<\/tr>\n<tr>\n<th>In-Band Y\u00f6netim<\/th>\n<td>200 Gb\/s&#8217;ye kadar, NVIDIA BlueField-3 DPU<\/td>\n<th>Out-of-Band Y\u00f6netim<\/th>\n<td>1G \/ 10G Ethernet<\/td>\n<\/tr>\n<tr>\n<th>G\u00fc\u00e7<\/th>\n<td>8x 1U 33 kW g\u00fc\u00e7 sistemi<\/td>\n<th>Toplam G\u00fc\u00e7<\/th>\n<td>132 kW<\/td>\n<\/tr>\n<tr>\n<th>In-Rack CDU<\/th>\n<td>250 kW kapasite<\/td>\n<th>Rack<\/th>\n<td>48U, 19&#8243;<\/td>\n<\/tr>\n<tr>\n<th>Boyutlar<\/th>\n<td>600 \u00d7 1068 \u00d7 2236 mm<\/td>\n<th>Ana Kullan\u0131m<\/th>\n<td>AI \/ Deep Learning Training ve Inference<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<h2>GPU ve Bellek Altyap\u0131s\u0131<\/h2>\n<div class=\"gtm-info\">\n<p>Sistem, 72 adet NVIDIA B300 GPU i\u00e7erir. Ayr\u0131ca 36 adet NVIDIA Grace CPU kullan\u0131r. Her GPU 288 GB HBM3e bellek sunar.<\/p>\n<p>Bunun yan\u0131nda toplam GPU belle\u011fi 21 TB&#8217;a kadar \u00e7\u0131kar. Sistem belle\u011fi ise 17 TB&#8217;a kadar LPDDR5X kapasitesine ula\u015f\u0131r. B\u00f6ylece Supermicro, GPU ve sistem belle\u011fini ayn\u0131 rack yap\u0131s\u0131nda toplar.<\/p>\n<\/div>\n<h2>NVLink ve A\u011f Altyap\u0131s\u0131<\/h2>\n<div class=\"gtm-info\">\n<p>Rack i\u00e7erisinde 9 adet NVLink Switch bulunur. Bu yap\u0131, 72 GPU aras\u0131nda y\u00fcksek h\u0131zl\u0131 ba\u011flant\u0131 kurar. Ayr\u0131ca GPU-to-GPU ba\u011flant\u0131 h\u0131z\u0131 1.8 TB\/s seviyesine ula\u015f\u0131r.<\/p>\n<p>Bunun yan\u0131nda sistem, compute fabric taraf\u0131nda NVIDIA Quantum-X800 InfiniBand veya Spectrum-X Ethernet kullanabilir. Ba\u011flant\u0131 h\u0131z\u0131 800 Gb\/s&#8217;ye kadar \u00e7\u0131kar. B\u00f6ylece y\u00fcksek h\u0131zl\u0131 veri aktar\u0131m\u0131 desteklenir.<\/p>\n<p>Ayr\u0131ca NVIDIA BlueField-3 DPU, in-band y\u00f6netim taraf\u0131nda 200 Gb\/s&#8217;ye kadar h\u0131z sa\u011flar. \u00d6te yandan out-of-band y\u00f6netim i\u00e7in 1G veya 10G Ethernet kullan\u0131l\u0131r.<\/p>\n<\/div>\n<h2>Depolama ve Rack Yap\u0131s\u0131<\/h2>\n<div class=\"gtm-info\">\n<p>SRS-GB300-NVL72, 144 adede kadar E1.S PCIe 5.0 s\u00fcr\u00fcc\u00fc yuvas\u0131 sunar. Ayr\u0131ca rack i\u00e7erisinde 18 adet 1U ARS-121GL-NB3 node yer al\u0131r.<\/p>\n<p>Bunun yan\u0131nda sistem 48U rack yap\u0131s\u0131n\u0131 kullan\u0131r. Rack geni\u015fli\u011fi 19 in\u00e7tir. Ayr\u0131ca fiziksel \u00f6l\u00e7\u00fcler 600 \u00d7 1068 \u00d7 2236 mm&#8217;dir.<\/p>\n<\/div>\n<h2>S\u0131v\u0131 So\u011futma ve G\u00fc\u00e7<\/h2>\n<div class=\"gtm-info\">\n<p>Sistem Direct Liquid Cooling teknolojisini kullan\u0131r. Ayr\u0131ca in-rack CDU kapasitesi 250 kW&#8217;a kadar \u00e7\u0131kar. Bunun yan\u0131nda sistem, redundant PSU ve \u00e7ift hot-swap pompa yap\u0131s\u0131 sunar.<\/p>\n<p>G\u00fc\u00e7 taraf\u0131nda 8 adet 1U 33 kW g\u00fc\u00e7 sistemi yer al\u0131r. Sonu\u00e7 olarak rack toplam 132 kW g\u00fc\u00e7 kapasitesi sa\u011flar.<\/p>\n<\/div>\n<h2>Kullan\u0131m Alan\u0131<\/h2>\n<div class=\"gtm-info\">\n<p>Supermicro, SRS-GB300-NVL72 i\u00e7in AI ve Deep Learning Training ile Inference i\u015f y\u00fcklerini \u00f6ne \u00e7\u0131kar\u0131r. Dolay\u0131s\u0131yla sistem, bu uygulamalara y\u00f6nelik rack-scale bir altyap\u0131 sunar.<\/p>\n<\/div>\n<h2>S\u0131k Sorulan Sorular<\/h2>\n<div class=\"gtm-faq\">\n<details>\n<summary>SRS-GB300-NVL72 ka\u00e7 GPU i\u00e7erir?<\/summary>\n<div class=\"gtm-faq-answer\">\nSistem 72 adet NVIDIA B300 GPU i\u00e7erir. Ayr\u0131ca 36 adet NVIDIA Grace CPU kullan\u0131r.\n<\/div>\n<\/details>\n<details>\n<summary>SRS-GB300-NVL72 ne kadar GPU belle\u011fi sunar?<\/summary>\n<div class=\"gtm-faq-answer\">\nRack seviyesinde 21 TB&#8217;a kadar HBM3e GPU belle\u011fi bulunur. Ayr\u0131ca her GPU 288 GB HBM3e bellek sunar.\n<\/div>\n<\/details>\n<details>\n<summary>SRS-GB300-NVL72 ka\u00e7 depolama yuvas\u0131 sunar?<\/summary>\n<div class=\"gtm-faq-answer\">\nSistem 144 adede kadar E1.S PCIe 5.0 s\u00fcr\u00fcc\u00fc yuvas\u0131 sunar. B\u00f6ylece rack seviyesinde y\u00fcksek kapasiteli depolama deste\u011fi sa\u011flar.\n<\/div>\n<\/details>\n<details>\n<summary>SRS-GB300-NVL72 hangi a\u011f altyap\u0131s\u0131n\u0131 kullan\u0131r?<\/summary>\n<div class=\"gtm-faq-answer\">\nSistem NVIDIA Quantum-X800 InfiniBand veya NVIDIA Spectrum-X Ethernet kullanabilir. Ayr\u0131ca compute fabric ba\u011flant\u0131s\u0131 800 Gb\/s&#8217;ye kadar \u00e7\u0131kabilir.\n<\/div>\n<\/details>\n<details>\n<summary>SRS-GB300-NVL72 hangi i\u015f y\u00fcklerine y\u00f6neliktir?<\/summary>\n<div class=\"gtm-faq-answer\">\nSupermicro, sistem i\u00e7in AI ve Deep Learning Training ile Inference i\u015f y\u00fcklerini \u00f6ne \u00e7\u0131kar\u0131r. Dolay\u0131s\u0131yla \u00fcr\u00fcn bu uygulamalara y\u00f6nelik rack-scale bir \u00e7\u00f6z\u00fcm sunar.\n<\/div>\n<\/details>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p><strong>Supermicro SRS-GB300-NVL72<\/strong>, NVIDIA GB300 Grace Blackwell Ultra Superchip mimarisini kullanan s\u0131v\u0131 so\u011futmal\u0131 48U rack-scale AI sistemidir. Sistem, 72 adet NVIDIA B300 GPU, 36 adet NVIDIA Grace CPU, 21 TB\u2019a kadar HBM3e GPU belle\u011fi ve 17 TB\u2019a kadar LPDDR5X sistem belle\u011fi sunar. 1.8 TB\/s GPU-to-GPU NVLink ba\u011flant\u0131s\u0131 ve 800 Gb\/s\u2019ye kadar a\u011f altyap\u0131s\u0131yla b\u00fcy\u00fck \u00f6l\u00e7ekli AI training ve inference i\u015f y\u00fckleri i\u00e7in geli\u015ftirilmi\u015ftir.<\/p>\n","protected":false},"featured_media":13839,"comment_status":"open","ping_status":"closed","template":"","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"product_brand":[44],"product_cat":[48,2458],"product_tag":[],"gtm_use_case":[],"class_list":["post-13838","product","type-product","status-publish","has-post-thumbnail","product_brand-supermicro","product_cat-gpu-server","product_cat-sivi-sogutmali-gpu-server","desktop-align-left","tablet-align-left","mobile-align-left","first","instock","taxable","shipping-taxable","product-type-simple"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Supermicro SRS-GB300-NVL72 | NVIDIA GB300 NVL72<\/title>\n<meta name=\"description\" content=\"Supermicro SRS-GB300-NVL72; 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