{"id":79,"date":"2026-06-14T16:55:58","date_gmt":"2026-06-14T16:55:58","guid":{"rendered":"https:\/\/rdp.in\/gpu-mart\/product\/rdp-hpc-cpu-compute-node-edge\/"},"modified":"2026-07-06T01:47:41","modified_gmt":"2026-07-06T01:47:41","slug":"draco-8-node-h200-hpc-cluster","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/draco-8-node-h200-hpc-cluster\/","title":{"rendered":"DRACO 8-Node H200 HPC Cluster"},"content":{"rendered":"<p>The DRACO 8-Node H200 HPC Cluster is a turnkey 8-node HPC cluster pairing CPU-forward compute with GPU acceleration \u2014 1536 AMD EPYC cores across 8 nodes plus H200 accelerators (4,512 GB HBM3e HBM3e, NVLink in-node) for large-model training and high-throughput inference, wired with a low-latency InfiniBand fabric. It runs traditional FP64\/MPI HPC and large-model AI on one cluster, on-premises, in INR, on a GST invoice.<\/p>\n<p>Engineered for engineering, research and analytics teams that need real HPC throughput with serious AI, it is delivered racked, cabled, scheduled and validated as a single system \u2014 RDP sizes the nodes, fabric, parallel storage, scheduler and cooling, with one warranty and one support contract.<\/p>\n<h3>Key highlights<\/h3>\n<ul>\n<li><strong>1536 EPYC cores across 8 nodes<\/strong> \u2014 serious CPU throughput for FP64, MPI and memory-bound HPC.<\/li>\n<li><strong>32\u00d7 H200 \u00b7 4,512 GB HBM3e<\/strong> \u2014 GPU acceleration for large-model AI training and inference alongside HPC.<\/li>\n<li><strong>InfiniBand NDR fabric<\/strong> \u2014 low-latency, high-bandwidth interconnect for tightly-coupled MPI jobs and collectives.<\/li>\n<li><strong>8 TB DDR5 ECC + 480 TB NVMe parallel NVMe<\/strong> \u2014 large memory and a high-throughput parallel filesystem.<\/li>\n<li><strong>Scheduler-ready, turnkey<\/strong> \u2014 delivered with Slurm\/Kubernetes, validated; one SKU, one warranty.<\/li>\n<li><strong>On-prem data sovereignty<\/strong> \u2014 codes, data and models stay in-house; DPDP-friendly, air-gappable.<\/li>\n<li><strong>Make-in-India OEM<\/strong> \u2014 predictable INR pricing, GST tax invoice (HSN 8471), pan-India onsite support, GeM-procurable.<\/li>\n<li><strong>Scale path<\/strong> \u2014 grow node count and step up the accelerator as workloads demand.<\/li>\n<\/ul>\n<h3>AI workload fit (what it actually runs \u2014 honestly)<\/h3>\n<ul>\n<li><strong>HPC + simulation (primary):<\/strong> FP64\/MPI workloads \u2014 CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo \u2014 across 1536 cores.<\/li>\n<li><strong>AI training &amp; inference:<\/strong> train and fine-tune large models across the NVLink-connected H200 GPUs, and serve them at high throughput alongside HPC jobs.<\/li>\n<li><strong>RAG &amp; agentic:<\/strong> production AI services co-located with HPC for engineering and research teams.<\/li>\n<li><em>Engineering note:<\/em> each node&#8217;s H200 GPUs are NVLink-connected for efficient in-node tensor parallelism, and nodes scale over InfiniBand \u2014 this cluster trains and serves large models alongside FP64 HPC. The CPU cores carry the simulation\/MPI side; the GPUs carry the AI side.<\/li>\n<\/ul>\n<h3>AI workload positioning<\/h3>\n<p>This sits at the <strong>HPC + AI training<\/strong> stage: a cluster for teams whose workload spans simulation\/analytics and large-model AI. With 1536 CPU cores and 32 accelerators on an InfiniBand fabric, it is sized to <strong>sustain<\/strong> real HPC throughput plus model training \u2014 where renting equivalent cloud HPC continuously gets expensive.<\/p>\n<h3>Industry use cases<\/h3>\n<ul>\n<li><strong>Manufacturing &amp; automotive<\/strong> \u2014 CFD\/FEA simulation plus AI-assisted design.<\/li>\n<li><strong>Energy &amp; engineering<\/strong> \u2014 reservoir, structural and process simulation.<\/li>\n<li><strong>BFSI<\/strong> \u2014 risk, Monte-Carlo and quantitative analytics with AI.<\/li>\n<li><strong>EDA &amp; semiconductors<\/strong> \u2014 chip design verification at scale.<\/li>\n<li><strong>Research &amp; academia<\/strong> \u2014 a shared HPC + AI cluster for departments.<\/li>\n<li><strong>Life sciences<\/strong> \u2014 molecular dynamics and bioinformatics pipelines.<\/li>\n<\/ul>\n<h3>Performance \u2014 and how to be sure<\/h3>\n<p>We don&#8217;t publish inflated peak numbers. The honest picture: 1536 EPYC cores and 32\u00d7 H200 on InfiniBand are sized for converged HPC + large-model AI. <strong>Want certainty? Request a free benchmark of your HPC codes and AI models, including an MPI scaling test, on this exact configuration before you buy<\/strong>; we&#8217;ll send back real performance and scaling efficiency.<\/p>\n<h3>Series &amp; upgrade path<\/h3>\n<ul>\n<li><strong>DRACO<\/strong> (flagship cluster tier) \u2014 <em>this<\/em>.<\/li>\n<li><strong>Node ladder:<\/strong> 4 \u2192 8 \u2192 16 \u2192 32 \u2192 64+ nodes; <strong>accelerator ladder:<\/strong> L40S (inference\/viz) \u2192 H200 (training).<\/li>\n<li><strong>When to step up:<\/strong> for the largest training, move to GPU Servers or a rack-scale system \u2014 talk to an architect.<\/li>\n<\/ul>\n<h3>On-prem vs cloud \u2014 the TCO case<\/h3>\n<p>For sustained HPC, owning beats renting: a continuously-running cloud HPC cluster adds up fast, and on-prem removes egress and keeps codes and data in-house. RDP pricing is fixed in INR with a GST input-credit-eligible invoice \u2014 ask for a <strong>3-year TCO comparison<\/strong>.<\/p>\n<h3>Software &amp; day-one readiness<\/h3>\n<p>Ships <strong>pre-integrated and validated<\/strong>: NVIDIA driver, CUDA, cuDNN, NCCL, MPI (OpenMPI\/MPICH), the InfiniBand stack, Slurm and\/or Kubernetes, with common HPC toolchains, PyTorch and vLLM \/ Triton on a supported Linux LTS. Optional managed cluster operations and an HPC\/MLOps platform.<\/p>\n<h3>Power, cooling &amp; rack integration<\/h3>\n<p>A 8-node cluster \u2014 RDP scopes rack power, cooling (air or liquid), the InfiniBand fabric and floor\/rack requirements in the design. <em>(Exact power, BTU, airflow and rack-depth figures confirmed on the build sheet.)<\/em> Full out-of-band management across the cluster.<\/p>\n<h3>Deployment, warranty &amp; support<\/h3>\n<ul>\n<li><strong>Made to order<\/strong>, integrated, racked, cabled and burned-in in India; lead time confirmed at quote.<\/li>\n<li><strong>Delivered as one system:<\/strong> nodes, fabric switches, cabling, PDUs, parallel storage, and the full HPC\/AI software stack.<\/li>\n<li><strong>Onsite warranty + AMC<\/strong> with pan-India coverage, cluster-level support and an RMA\/escalation path <em>(exact terms confirmed at quote)<\/em>.<\/li>\n<\/ul>\n<h3>Why RDP<\/h3>\n<p>14 years of Make-in-India infrastructure and <strong>300,000+ devices shipped<\/strong>. Indian OEM, INR pricing, GST tax invoice (HSN 8471), pan-India onsite engineers, GeM availability, and DPDP \/ sovereign-AI-ready deployment.<\/p>\n<h3>Buy with confidence<\/h3>\n<p>This is a turnkey HPC + AI cluster, made to order \u2014 <strong>talk to an RDP solution architect<\/strong>, size the nodes, accelerators and fabric for your codes, get a 3-year TCO, and <strong>benchmark your own workloads before you commit.<\/strong> Request a quote to begin.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>8 nodes \u00b7 16\u00d7 AMD EPYC 9005 (1,536 cores) \u00b7 8 TB DDR5 ECC \u00b7 32\u00d7 H200 \u00b7 480 TB NVMe \u00b7 InfiniBand \u00b7 liquid\/air<\/p>\n","protected":false},"featured_media":2101,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"DRACO 8-Node H200 HPC Cluster \u2014 1536 EPYC cores, 32\u00d7 H200 | RDP GPU Mart","rank_math_description":"Turnkey on-prem HPC + AI cluster \u2014 8 nodes, 1536 EPYC cores, 32\u00d7 H200 (4,512 GB HBM3e), InfiniBand. Run FP64\/MPI HPC and AI on-prem. Make-in-India, GST invoice. 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