Cisco C880A M8 CON-L1NCO-UCSC88A8 8x GPU Server | Enterprise — CON-L1NCO-UCSC88A8

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SKU
CON-L1NCO-UCSC88A8
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Move compute bottlenecks out of the way with a Cisco C880A M8 configuration designed for accelerated workloads. With 8 B300 GPUs, dual AMD EPYC 6767P processors, and 8 CX connections, this system is aimed at teams running AI training, simulation, analytics, and other workloads that depend on parallel processing and fast data movement. The value here is density with purpose. Instead of spreading acceleration across multiple smaller systems, this platform concentrates GPU capacity into a single enterprise-class node, simplifying rack planning and reducing the operational overhead of managing fragmented compute islands. Dual processors provide the CPU side needed to feed the accelerators, while the CX connectivity supports the high-throughput fabric these environments demand. For organizations investing in AI infrastructure, this is the kind of server that justifies its footprint by doing the work of several conventional systems. It is built for environments where performance per rack unit, interconnect design, and deployment consistency matter as much as raw compute count. Ideal For AI training node for model development and fine-tuning Simulation platform for engineering and research workloads High-throughput analytics server for data-intensive pipelines GPU-accelerated compute node in enterprise data centers Why This Product 1 8 GPU design offers far more acceleration than standard CPU-only servers 2 Dual AMD EPYC processors help keep GPUs fed with data 3 8 CX connections support high-bandwidth infrastructure planning 4 Single-node density reduces the need for multiple smaller systems
  • Processor Count: 2
  • Processor Model: AMD EPYC 6767P
  • Processor Family: AMD EPYC
  • Server Form Factor: Rack Mount
  • Key Feature 1: Cisco C880A M8 enterprise accelerator platform
  • Key Feature 2: 8 B300 GPU configuration
  • Key Feature 3: 2 AMD EPYC 6767P processors
  • Key Feature 4: 8 CX connectivity points
  • Key Feature 5: Built for GPU-accelerated compute workloads
  • Key Feature 6: Designed for dense enterprise deployment
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