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GIGABYTE R243-EG0-AAL1, Sockel SP6, AMD EPYC 8005-Serie, AMD EPYC 8004, GDDR5, Hexa-Kanal, 2,5, 3,5, M.2, HDD & SSD
Artikelnummer: [25039858] | Produzent: Gigabyte Technology | Modell nummer: 6NR243EG0DR000AAL1 | EAN: 4719331856359
Externen Lager (7-9 Werktage)
Das Produkt befindet sich in einem externen Lager. Die Lieferfrist: ca. 7-9 Werktage.. Mehr Info
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Big Performance | Low Power | Small Footprint
Optimized for edge, telco, and cloud storage environments, the AMD's SP6 (LGA 4844) socket, powering AMD EPYC 8005 and 8004 Server processors, delivers a balance of energy efficiency and cost performance. Built to maximize performance/watt and performance/$, the 8005/8004 CPUs retain core EPYC capabilities, including multithreading, hardware root of trust, and DDR5 memory with ECC support. The latest EPYC 8005 processors further raise the bar with up to 84 cores, 168 threads, and support for 6400 MT/s DDR5, enabling higher compute density in space- and power-constrained deployments.
Purpose-built for modern distributed infrastructure, AMD's SP6 platform excels in remote deployments, software-defined storage (SDS), and decentralized fault tolerance, where workloads must run efficiently at the edge, scale seamlessly across distributed data planes, and remain resilient in the face of node or network disruptions.
Optimized for edge, telco, and cloud storage environments, the AMD's SP6 (LGA 4844) socket, powering AMD EPYC 8005 and 8004 Server processors, delivers a balance of energy efficiency and cost performance. Built to maximize performance/watt and performance/$, the 8005/8004 CPUs retain core EPYC capabilities, including multithreading, hardware root of trust, and DDR5 memory with ECC support. The latest EPYC 8005 processors further raise the bar with up to 84 cores, 168 threads, and support for 6400 MT/s DDR5, enabling higher compute density in space- and power-constrained deployments.
Purpose-built for modern distributed infrastructure, AMD's SP6 platform excels in remote deployments, software-defined storage (SDS), and decentralized fault tolerance, where workloads must run efficiently at the edge, scale seamlessly across distributed data planes, and remain resilient in the face of node or network disruptions.