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ASUS ESC8000A-E12P-3W10G is a 4U dual AMD EPYC 9004 GPU server with up to 8 GPUs, DDR5 memory, and PCIe 5.0 for AI, deep learning, and HPC environments.
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The ASUS ESC8000A-E12P-3W10G (SKU: ESC8000A-E12P-3W10G) is a high-density 4U GPU server designed for AI training, deep learning, and high-performance computing environments. It combines dual AMD EPYC 9004 processors with large-scale GPU acceleration in a PCIe Gen5 architecture.
This platform supports up to two AMD EPYC 9004 series processors using Socket SP5. As a result, it delivers high core density and strong parallel processing for AI and HPC workloads. In addition, it includes 24 DDR5 DIMM slots. It supports RDIMM memory up to 6TB with speeds up to 4800 MT/s. Therefore, it provides high memory bandwidth and capacity for data-intensive applications.
The system supports up to 8× rear dual-slot PCIe 5.0 GPUs. It also includes an additional front-access PCIe 5.0 slot. As a result, it enables large-scale GPU acceleration for AI training, inference, and simulation workloads. The PCIe Gen5 architecture ensures high-speed data transfer between CPUs, GPUs, and storage.
For storage, the server includes 8× 3.5″ drive bays with support for SATA and NVMe drives. It uses an integrated SATA 6Gbps controller. As a result, it offers flexible storage configurations for datasets and application storage.
For networking, the system provides 2× 1GbE ports for standard connectivity. It also supports additional high-speed networking via PCIe expansion. Therefore, it allows integration into high-bandwidth data center environments.
The platform supports multiple PCIe Gen5 expansion slots for GPUs and adapters. It is optimized for thermal efficiency and airflow to maintain stable performance under heavy GPU workloads.
For reliability, the server includes 4× hot-swappable 2600W/3000W 80 PLUS Titanium power supplies in a 2+2 redundant configuration. It also features a dedicated RJ45 management port for remote monitoring and control. Therefore, it ensures high availability and efficient system management.
This system is suitable for AI data centers, research labs, and enterprise HPC deployments. It supports large-scale AI training, deep learning, and GPU-accelerated computing workloads.
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