GP-AORUS WATERFORCE X II 360
Server Motherboard
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.
Rack Server
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.
Tower Server / Workstation
Stand-alone chassis for customers to customize and expand as needs change.
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.
ARM Server
Arm architecture servers will compete in Cloud to Edge as they tackle compute-bound workloads.
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 Server
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 Server
Software defined cluster of nodes can be dedicated for compute, storage, networking, or virtualization.
Storage Server
Capacity, reliability, and storage flexibility are built into these storage servers for enterprise and datacenters.
Network Server
Securely manage the use of files and applications for office environments while storing large amounts of data.
Hybrid/Private Cloud Server
Server resources are effectively allocated via virtualization, and these servers are highly flexible.
Edge Server
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.
