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AMD EPYC UP Server Board 7000 8-Ch DDR4

Tillverkare: GIGABYTE
ID: MZ01-CE1
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Produktspecifikation
Beskrivning
På lager i butiker
Leverans
Prisutveckling
Processor
ProcessortillverkareAMD
ProcessorfamiljAMD EPYC
ProcessorsockelSP3
Minne
Minnesplatser1
Maximalt internminne128 GB
Minnets hastigheter2133,2400,2666 MHz
Minnestyper som stödsDDR4
Antal minnesplatser1
Miljökrav
Intervall för relativ operativ luftfuktighet8 - 80%
Temperaturintervall (förvaring)-40 - 60 ° C
Temperatur vid drift10 - 40 ° C
Fuktighet (förvaring)20 - 95%
Nätverk
Nätverksansluten (Ethernet)checkmark
Wi-Ficross
Intern I/O
Antalet COM-anslutningar2
ATX strömkontakt (24-pin)checkmark
TPM-anslutningcheckmark
EPS strömkontakt (8-polig)checkmark
USB 3.2 Gen 1 (3.1 Gen 1)-anslutningar1
Antal SATA III kontakter4
Anslutningsmöjligheter
Antal LAN (RJ-45) anslutningar2
Kvalitet på VGA (D-Sub) porten1
Antal USB 3.2 Gen 1 (3.1 Gen 1) typ A-portar2
Lagringskontroll
Lagringsenhetsgränssnitt som stödsM.2, SlimSAS
Förpackning
Låddjup330 mm
Höjd80 mm
Förpackningens bredd360 mm
Expansionsplatser
PCI Express x8 (Gen 3.x)-kortplatser1
PCI Express x16 (Gen 3.x)-kortplatser4
Antal M.2 (M)-platser1
Grafiken
Ombord grafikkort modellAspeed AST2500
Egenskaper
Moderkort formfaktorATX
Produktens färgBlå
Kompatibla operativsystemWindows Server 2012 R2 with Update
Windows Server 2016

Red Hat Enterprise Linux 7.4 (x64) or later
Red Hat Enterprise Linux 8.0 (x64) or later
Red Hat Enterprise Linux 9.0 (x64) or later

SUSE Linux Enterprise Server 11 SP4 (x64) or later
SUSE Linux Enterprise Server 12 SP3 (x64) or later
SUSE Linux Enterprise Server 15 (x64) or later

Ubuntu 16.04 LTS (x64) or later
Ubuntu 18.04 LTS (x64) or later
Ubuntu 20.04 LTS (x64) or later

VMware ESXi 6.5 Update1 or later
VMware ESXi 6.7 or later
VMware ESXi 7.0 or later
VMware ESXi 8.0 or later

Citrix Xenserver 7.1.0 CU2 or later
Citrix Xenserver 7.4.0 or later
Citrix Hypervisor 8.0.0 or later
Moderkort, chipsetfamiljAMD
Komponent förServer
EAN8592978174569
AMD EPYC™ Processors
The New x86 Option
AMD’s return to the CPU segment delivers a whole new value proposition to the x86 world. Built on GIGABYTE’s extensive design expertise across a range of chipset platforms, this AMD EPYC™ platform is already receiving acclaim for its high specification:

Memory
I/O
Network connectivity
This platform is intended as an alternative for builders in the x86 space and packs a real punch in flexibility and expansion options.

Comprehensive I/O
Both single- and dual-socket CPUs come equipped with 128x PCIe lanes, providing extensive I/O options. This is a huge improvement in I/O vs. incumbent x86 offerings.
Increased I/O allows for flexibility in extending your storage, networking or compute to a level previously unattainable with standard server motherboards.
In addition, the integrated nature of the processor – designed as a system-on-chip (SoC) - means that there is no need for a separate PCH and less additional switches needed for expansion lanes.

Dense, High Speed Storage Support
Onboard M.2
GIGABYTE AMD EPYC™ platforms are designed to support on-board ‘M.2’ storage devices for time-sensitive operations and leaves room on the standard storage for compute tasks. Delivering up to 32 Gb/s data transfer speeds, M.2 offers users considerably faster storage performance than current mSATA devices.

Data Security
TPM 2.0 Module*
GIGABYTE’s EPYC™ platform is designed to support Trusted Platform Modules (TPM - discrete cryptographic on-board processors).

Carefully Selected Components
GIGABYTE’s passive components are carefully selected to guarantee a stable operating environment and allow the processors and the memory to deliver their maximum performance. GIGABYTE’s server motherboards are built with long lasting components for a high degree of reliability and durability.

NVIDIA® V100 Tensor Core GPU Support
GIGABYTE’s AMD EPYC server systems and motherboards are fully compatible and qualified to use with NVIDIA® V100 Tensor Core GPUs, an advanced data center GPU built to accelerate AI, HPC, and graphics. Powered by NVIDIA Volta™ architecture and with 640 Tensor Cores, the NVIDIA V100 has broken the 100 teraflops (TFLOPS) barrier of deep learning performance — enabling data scientists, researchers, and engineers to tackle challenges that were once impossible.
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