{"product_id":"graphics-card-mi50-32g-computing-gpu-acceleration-card","title":"Graphics Card MI50 32G Computing GPU Acceleration Card","description":"\u003ch1\u003eSPECIFICATIONS\u003c\/h1\u003e\u003cp\u003e\u003cspan\u003eAC Voltage\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e115\/120 V\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eBrand Name\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eNONE\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eCarry width\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e4096bit\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eCertification\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003ece\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eChip factory\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eAMD\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eDo you support one-piece delivery?\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003esupport\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eEfficiency\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eIE 1\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eHigh-concerned chemical\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eNone\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eMemory capacity\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e32gb\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eMemory frequency\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e1000MHz\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eNumber of assembly lines\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e3840\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003eOrigin\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eMainland China\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003echip process\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e7nm\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003ecore frequency\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e1200MHz\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003ememory width\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e4096bit\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003estream processor unit\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003e3840\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003etype\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eProfessional grade\u003c\/span\u003e\u003c\/p\u003e\u003cp\u003e\u003cspan\u003evideo memory type\u003c\/span\u003e: \u003cspan style=\"color:#333\"\u003eHBM2\u003c\/span\u003e\u003c\/p\u003e\u003cdiv class=\"detailmodule_html\"\u003e\u003cdiv class=\"detail-desc-decorate-richtext\"\u003e\n\u003cdiv id=\"offer-template-0\"\u003e\n\u003cimg cke-id=\"img54\" referrerpolicy=\"no-referrer\" src=\"https:\/\/ae01.alicdn.com\/kf\/Sff35f26c496b4d83b99318c534c4d245D.jpg\"\u003e \u003cimg cke-id=\"img55\" referrerpolicy=\"no-referrer\" src=\"https:\/\/ae01.alicdn.com\/kf\/S6d96101b46cc411dac0898db243940eaa.jpg\"\u003e \u003cimg cke-id=\"img56\" referrerpolicy=\"no-referrer\" src=\"https:\/\/ae01.alicdn.com\/kf\/S0fdd82606deb454484ad7f452265b264Z.jpg\"\u003e \u003cimg cke-id=\"img57\" referrerpolicy=\"no-referrer\" src=\"https:\/\/ae01.alicdn.com\/kf\/S4aa80db2ec8147b7a45c14218dd139a3E.jpg\"\u003e \u003cimg cke-id=\"img58\" referrerpolicy=\"no-referrer\" src=\"https:\/\/ae01.alicdn.com\/kf\/Sed2f5902a0ac4a7988b3ffd745d7b8a0S.jpg\"\u003e \u003cimg cke-id=\"img59\" referrerpolicy=\"no-referrer\" src=\"https:\/\/ae01.alicdn.com\/kf\/S5e1449953a7f47339f600640f3417f27P.jpg\"\u003e\n\u003c\/div\u003e\n\n\u003cdiv style=\"width: 790.0px;\"\u003e\n\u003cdiv class=\"rich-text-component\" style=\"width: 395.0px;padding: 10.0px;word-break: break-all;white-space: break-spaces;font-family: ali-webfont;zoom: 2;font-size: 0.0px;box-sizing: border-box;\"\u003e\n\u003ch3\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eFirst, the core parameters\u003c\/strong\u003e\u003c\/h3\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eArchitecture and process\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eAdopt 7nm process technology, based on GCN 5.1 architecture.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eThe core code is Vega20, the number of transistors is 13.20 billion, and the core area is 331mm ².\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eFrequency and computing power\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eBase frequency 1200MHz, acceleration frequency 1746MHz.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eFP32 single-precision floating-point performance is about 13.4 TFLOPS, FP64 double-precision is about 6.7 TFLOPS.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eStream Processor and Cache\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eThe number of stream processors is 3840, the L1 cache is 16KB, and the L2 cache is 4MB.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eSecond, video memory configuration\u003c\/strong\u003e\u003c\/h3\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eMemory capacity and type\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\n\u003cstrong style=\"font-size: 12.0px;\"\u003eofficial parameters\u003c\/strong\u003e\u003cspan style=\"font-size: 12.0px;\"\u003e: The standard version MI50 is 16GB HBM2 video memory, with a memory width of 4096bit and a bandwidth of 1TB\/s.\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli class=\"ql-indent-1\"\u003e\n\u003cstrong style=\"font-size: 12.0px;\"\u003eMarket customized version\u003c\/strong\u003e\u003cspan style=\"font-size: 12.0px;\"\u003e: 32GB video memory.\u003c\/span\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eMemory frequency\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eThe video memory base frequency is 1000MHz (equivalent to 2Gbps), and the actual bandwidth depends on the HBM2 stack configuration.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eIII, Interface and Extension\u003c\/strong\u003e\u003c\/h3\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003ephysical interface\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eOutput interface: 1 mini-DisplayPort 1.4a.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003ePower supply interface: dual 8-pin power supply, the whole card TDP power consumption is 300W.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eextended support\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eSupports PCIe 4.0 bus, providing higher data transmission efficiency.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eSupport AMD Infinity Fabric Link technology to improve the efficiency of multi-card interconnection.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eIV. Application scenarios and performance\u003c\/strong\u003e\u003c\/h3\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eComputing and AI performance\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eSuitable for deep learning training, local large model inference (such as Qwen, DeepSeek, etc.), about 12-13 tokens\/s in the measured Win + Vulkan environment, and up to 15 tokens\/s in the Linux + ROCm environment.\u003c\/span\u003e\u003c\/li\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eCompared with the RTX 3060, the performance of some scenarios is improved by more than 30%.\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003col\u003e\n\u003cli\u003e\u003cstrong style=\"font-size: 12.0px;\"\u003eGame and rendering\u003c\/strong\u003e\u003c\/li\u003e\n\u003c\/ol\u003e\n\n\u003cul\u003e\n\u003cli class=\"ql-indent-1\"\u003e\u003cspan style=\"font-size: 12.0px;\"\u003eBrush into the custom BIOS, Master Lu runs 38- 440,000, can smoothly run \"Black Myth: Wukong\" and other games (high image quality 60 frames +).\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003e \u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/div\u003e\r\n","brand":"Amjad Traders","offers":[{"title":"Default Title","offer_id":54875246264692,"sku":"1005011691035242-Default Title","price":572134.99,"currency_code":"PKR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1001\/4212\/1332\/files\/Sff35f26c496b4d83b99318c534c4d245D.webp?v=1782930457","url":"https:\/\/cloudcomsys.com\/products\/graphics-card-mi50-32g-computing-gpu-acceleration-card","provider":"Cloudcom Systems","version":"1.0","type":"link"}