솔루션
솔루션 찾기 & FAQ
May 1, 2013
Hibernate failed under Win ME?
Please update bios to version F6 or later.
서버 메인보드
Server motherboards for demanding applications come in form factors: EEB/E-ATX/ATX/microATX/mini-ITX.
Workstation Motherboard
Professionals that work in AI, animation, and data science rely on solid, scalable, and performant workstation boards.
랙 서버
Innovation and performance are in these optimal rack servers to be deployed in data centers with demanding applications.
GPU Server
Scalable parallel computing GPU dense servers that are built for high performance.
High Density Server
Compute, Storage, and Networking are possible in high density, multi-node servers at lower TCO and greater efficiency.
타워 서버
Stand-alone chassis for customers to customize and expand as needs change.
Direct Liquid Cooling
Ensure peak performance in all configurations. Adopt direct-to-chip liquid cooling for the rising AI/HPC era.
Single-Phase Immersion Cooling
Address rising server heat with submerged cooling. Embrace next-gen liquid cooling for improved TCO and PUE.
Data Center - OCP
Based on OCP Open Rack Standards, barebone racks and nodes for datacenters.
x86
Tried and true x86 architecture based servers with support for the latest Intel and AMD processors.
AI Platform
Processing power, large amounts of data, fast networking, and accelerators all bundle into a scale out ready HPC and/or AI server solution.
Visual Computing
Systems that do visual applications from computer graphics to computer animation rely on visual computing servers.
High-Performance Computing Servers
Processing power, large amounts of data, fast networking, and accelerators all bundle into a scale out ready HPC and/or AI server solution.
Hyper-Converged Servers
Software defined cluster of nodes can be dedicated for compute, storage, networking, or virtualization.
스토리지 서버
Capacity, reliability, and storage flexibility are built into these storage servers for enterprise and datacenters.
Network Servers
Securely manage the use of files and applications for office environments while storing large amounts of data.
Hybrid/Private Cloud Servers
Server resources are effectively allocated via virtualization, and these servers are highly flexible.
Edge Servers
Real time data processing at the source is required for edge computing with reduced latency for Internet of Things (IoT) and 5G networks as they use cloud.
e-Mobility
Telematics and Edge computing platform for Electric vehicle, Autonomous driving, ADAS, ITS, and V2X applications
