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HPC Server & Cluster Specifications (Computing)
Modern HPC systems are designed for massive parallel processing, typically used in AI training, climate modeling, and genomic sequencing.
Google Cloud
Google Cloud
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Processor (CPU): Often dual-socket configurations using AMD EPYC 9004 series or Intel Xeon Scalable processors. High-end nodes may feature 128 cores per socket with support for AVX-512 instruction sets.
Accelerators (GPU): Vital for intensive math and ML. Common setups include multiple NVIDIA H100 (80GB), A100, or L40S GPUs per node.
Memory (RAM): Ranges from 256GB for standard compute nodes to over 2TB for "Big Memory" nodes, often using DDR5 4800MHz ECC RAM.
Networking (Interconnect): Low-latency, high-bandwidth connections like 200Gb HDR InfiniBand or 100Gb/s Omni-Path are standard for node-to-node communication.
Storage: Large-scale clusters utilize parallel file systems (like Lustre) with usable space often exceeding 18 PiB and throughput rates of 30 GB/s