{"id":82,"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-xl\/"},"modified":"2026-07-06T01:47:42","modified_gmt":"2026-07-06T01:47:42","slug":"draco-64-node-h200-hpc-cluster","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/draco-64-node-h200-hpc-cluster\/","title":{"rendered":"DRACO 64-Node H200 HPC Cluster"},"content":{"rendered":"<p>The DRACO 64-Node H200 HPC Cluster is a turnkey 64-node HPC cluster pairing massive CPU-forward compute with large-scale GPU acceleration \u2014 12288 AMD EPYC cores across 64 nodes plus 256\u00d7 H200 accelerators (36,096 GB HBM3e HBM3e, NVLink in-node), wired with a non-blocking 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 organisations whose workload spans serious simulation and 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>12288 EPYC cores across 64 nodes<\/strong> \u2014 large-scale CPU throughput for FP64, MPI and memory-bound HPC.<\/li>\n<li><strong>256\u00d7 H200 \u00b7 36,096 GB HBM3e<\/strong> \u2014 large-scale GPU acceleration for model training and high-throughput inference alongside HPC.<\/li>\n<li><strong>Non-blocking InfiniBand NDR fabric<\/strong> \u2014 full-bisection bandwidth for tightly-coupled MPI jobs and distributed training.<\/li>\n<li><strong>64 TB DDR5 ECC + 4 PB NVMe parallel NVMe<\/strong> \u2014 large memory and a high-throughput parallel filesystem at cluster scale.<\/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 toward supercomputer scale, or specialise into GPU-dense rack-scale systems.<\/li>\n<\/ul>\n<h3>AI workload fit (what it actually runs \u2014 honestly)<\/h3>\n<ul>\n<li><strong>HPC + simulation (primary):<\/strong> large FP64\/MPI workloads \u2014 CFD, FEA, molecular dynamics, EDA, risk and Monte-Carlo \u2014 across 12288 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.<\/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 a non-blocking InfiniBand spine \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. We validate real MPI and AI scaling on your codes rather than quoting a peak number.<\/li>\n<\/ul>\n<h3>AI workload positioning<\/h3>\n<p>This sits at the <strong>HPC + AI-training<\/strong> stage at cluster scale: a system for organisations running both large simulation and large-model AI. With 12288 CPU cores and 256 H200 GPUs on a non-blocking fabric, it is sized to <strong>sustain<\/strong> real HPC throughput plus model training \u2014 the owned alternative to renting hyperscale HPC.<\/p>\n<h3>Industry use cases<\/h3>\n<ul>\n<li><strong>Manufacturing &amp; automotive<\/strong> \u2014 large-scale CFD\/FEA plus AI-assisted design.<\/li>\n<li><strong>Energy &amp; engineering<\/strong> \u2014 reservoir, structural and process simulation at scale.<\/li>\n<li><strong>BFSI<\/strong> \u2014 large 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>Government &amp; research<\/strong> \u2014 a shared institutional HPC + AI cluster.<\/li>\n<li><strong>Life sciences<\/strong> \u2014 large 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: 12288 EPYC cores and 256\u00d7 H200 on a non-blocking fabric are sized for large-scale converged HPC + AI. <strong>Want certainty? Request a free benchmark of your HPC codes and AI models, including an MPI and distributed-training scaling test, on a representative 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> up to 64+ nodes; <strong>accelerator ladder:<\/strong> L40S (inference\/viz) \u2192 H200 (training).<\/li>\n<li><strong>When to step up:<\/strong> for the largest AI training, move to GPU-dense rack-scale systems or a supercomputer \u2014 talk to an architect.<\/li>\n<\/ul>\n<h3>On-prem vs cloud \u2014 the TCO case<\/h3>\n<p>For sustained large-scale HPC, owning beats renting decisively: a continuously-running cloud HPC cluster of this size dominates an engineering budget, 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 64-node liquid-cooled cluster with substantial power density \u2014 RDP scopes facility power, cooling, the InfiniBand spine and floor\/rack requirements in the design. <em>(Exact power, BTU, flow 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, cooled and burned-in in India; project timeline confirmed at quote.<\/li>\n<li><strong>Delivered as one system:<\/strong> nodes, leaf\/spine 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 SLAs 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 large-scale 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>64 nodes \u00b7 128\u00d7 AMD EPYC 9005 (12,288 cores) \u00b7 64 TB DDR5 ECC \u00b7 256\u00d7 H200 \u00b7 4 PB NVMe \u00b7 InfiniBand \u00b7 liquid-cooled<\/p>\n","protected":false},"featured_media":1932,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"DRACO 64-Node H200 HPC Cluster \u2014 12288 EPYC cores, 256\u00d7 H200 | RDP GPU Mart","rank_math_description":"Turnkey on-prem large-scale HPC + AI cluster \u2014 64 nodes, 12288 EPYC cores, 256\u00d7 H200 (36,096 GB HBM3e), non-blocking InfiniBand, liquid-cooled. Make-in-India, GST invoice. 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