{"id":83,"date":"2026-06-14T16:55:58","date_gmt":"2026-06-14T16:55:58","guid":{"rendered":"https:\/\/rdp.in\/gpu-mart\/product\/rdp-reference-supercomputer-lite\/"},"modified":"2026-07-06T01:47:41","modified_gmt":"2026-07-06T01:47:41","slug":"draco-512x-gh200-ai-supercomputer","status":"publish","type":"product","link":"https:\/\/rdp.in\/gpu-mart\/product\/draco-512x-gh200-ai-supercomputer\/","title":{"rendered":"DRACO 512\u00d7 GH200 AI Supercomputer"},"content":{"rendered":"<p>The DRACO 512\u00d7 GH200 AI Supercomputer is a turnkey, liquid-cooled HPC + AI supercomputer built on 512 NVIDIA GH200 Grace-Hopper accelerators, delivering ~74 TB HBM3e of aggregate accelerator memory across a multi-rack system with a non-blocking InfiniBand spine. It is engineered for organisations that need both traditional HPC (simulation, FP64) and frontier AI on one machine \u2014 on-premises, in INR, on a GST invoice.<\/p>\n<p>Delivered as a single engagement, RDP designs the reference architecture, integrates, cools and burns it in, and hands over one validated supercomputer with one warranty and one support contract \u2014 removing multi-vendor integration risk. Its defining strength: tightly-coupled Grace CPU + Hopper GPU with coherent memory for HPC + AI.<\/p>\n<h3>Key highlights<\/h3>\n<ul>\n<li><strong>512\u00d7 GH200 \u00b7 ~74 TB HBM3e aggregate<\/strong> \u2014 accelerator memory for large simulations and frontier AI.<\/li>\n<li><strong>NVLink-C2C + non-blocking InfiniBand<\/strong> \u2014 NVLink-C2C coherent CPU-GPU links and a non-blocking InfiniBand spine between superchips.<\/li>\n<li><strong>HPC + AI convergence<\/strong> \u2014 strong FP64\/HPC throughput alongside mixed-precision AI on one system.<\/li>\n<li><strong>512\u00d7 Grace (ARM) + Grace LPDDR5X coherent memory<\/strong> \u2014 CPU and memory matched to 512 accelerators.<\/li>\n<li><strong>8 PB parallel NVMe parallel filesystem<\/strong> \u2014 high-throughput storage for datasets, checkpoints and simulation output.<\/li>\n<li><strong>Multi-Rack, liquid-cooled, turnkey<\/strong> \u2014 delivered, integrated and validated; one engagement, one warranty.<\/li>\n<li><strong>On-prem data sovereignty<\/strong> \u2014 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<\/ul>\n<h3>AI workload fit (what it actually runs \u2014 honestly)<\/h3>\n<ul>\n<li><strong>HPC + simulation:<\/strong> FP64 scientific computing (CFD, weather, molecular dynamics, finite-element) alongside AI.<\/li>\n<li><strong>Frontier AI training:<\/strong> distributed training of large models across the 512 accelerators with 3D parallelism.<\/li>\n<li><strong>Large-scale inference &amp; fine-tuning:<\/strong> serve and fine-tune many large models in parallel.<\/li>\n<li><em>Engineering note:<\/em> this is an NVIDIA Grace-Hopper system on the CUDA software stack. At this scale the network and parallelism strategy decide real performance; we run a scaling test on your codes and models rather than quoting a peak number.<\/li>\n<\/ul>\n<h3>AI workload positioning<\/h3>\n<p>This sits at the <strong>HPC + foundation-model<\/strong> convergence: a supercomputer that runs both scientific simulation and frontier AI. With ~74 TB HBM3e of accelerator memory on a non-blocking fabric, it is sized to <strong>sustain<\/strong> mixed HPC\/AI workloads on-prem \u2014 the sovereign, owned alternative to renting hyperscale capacity.<\/p>\n<h3>Industry use cases<\/h3>\n<ul>\n<li><strong>Government &amp; national labs<\/strong> \u2014 a sovereign HPC + AI supercomputer on GeM-procurable infrastructure.<\/li>\n<li><strong>Weather, climate &amp; energy<\/strong> \u2014 large FP64 simulation plus AI surrogates.<\/li>\n<li><strong>Pharma &amp; life sciences<\/strong> \u2014 molecular dynamics, drug discovery and AI in one system.<\/li>\n<li><strong>Aerospace, automotive &amp; manufacturing<\/strong> \u2014 CFD\/FEA simulation plus AI design.<\/li>\n<li><strong>Academia &amp; research<\/strong> \u2014 a shared institutional supercomputer for HPC and AI.<\/li>\n<li><strong>Neocloud \/ HPC providers<\/strong> \u2014 a converged HPC+AI service platform.<\/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: 512 GH200 accelerators (~74 TB HBM3e) on a non-blocking fabric are sized for converged HPC + AI at scale. <strong>Want certainty? Request a free benchmark \u2014 your HPC codes and AI models, including a scaling test \u2014 on a representative configuration before you commit<\/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 supercomputer tier) \u2014 <em>this<\/em>.<\/li>\n<li><strong>Scale ladder:<\/strong> from a few hundred accelerators to exascale-class systems (thousands of accelerators).<\/li>\n<li><strong>Architecture options:<\/strong> NVIDIA Grace-Hopper, AMD Instinct MI300X\/MI300A \u2014 chosen to fit your codes and software stack.<\/li>\n<li><strong>When to step up:<\/strong> extend to a larger data hall \u2014 co-design the fabric, power and facility with an RDP architect.<\/li>\n<\/ul>\n<h3>On-prem vs cloud \u2014 the TCO case<\/h3>\n<p>At supercomputer scale, owning is a strategic and economic decision: an always-on hyperscale cloud system dominates any budget over a multi-year horizon, while on-prem removes egress and keeps sovereign data and codes in-house. RDP pricing is fixed in INR with a GST input-credit-eligible invoice \u2014 ask for a <strong>multi-year TCO and financing model<\/strong>.<\/p>\n<h3>Software &amp; day-one readiness<\/h3>\n<p>Ships <strong>pre-integrated and validated<\/strong>: NVIDIA driver, CUDA, cuDNN, NCCL, the InfiniBand stack, Slurm and\/or Kubernetes, with PyTorch and vLLM \/ Triton \/ TensorRT-LLM on Ubuntu LTS, with monitoring and a scheduler. Optional managed operations and an HPC\/MLOps platform.<\/p>\n<h3>Power, cooling &amp; rack integration<\/h3>\n<p>A multi-rack liquid-cooled supercomputer with high power density \u2014 RDP scopes facility power, CDU\/manifold and water, the InfiniBand spine, floor layout and redundancy in the reference-architecture design. <em>(Exact power, BTU, flow and facility figures confirmed in the design package.)<\/em> Full out-of-band management.<\/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, cooling, parallel storage, and the full HPC\/AI software stack.<\/li>\n<li><strong>Onsite warranty + AMC<\/strong> with pan-India coverage, system-level SLAs and an 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 supercomputer, made to order \u2014 <strong>talk to an RDP solution architect<\/strong>, co-design the architecture for your codes and models, get a multi-year TCO, and <strong>run a benchmark before you commit.<\/strong> Request a quote to begin.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>512\u00d7 GH200 \u00b7 512\u00d7 Grace (ARM) \u00b7 Grace LPDDR5X coherent memory \u00b7 8 PB parallel NVMe \u00b7 Multi-Rack \u00b7 liquid-cooled<\/p>\n","protected":false},"featured_media":1767,"comment_status":"open","ping_status":"closed","template":"","meta":{"_yoast_wpseo_title":"","_yoast_wpseo_metadesc":"","rank_math_title":"DRACO 512\u00d7 GH200 AI Supercomputer \u2014 ~74 TB HBM3e, HPC + AI | RDP GPU Mart","rank_math_description":"Turnkey on-prem HPC + AI supercomputer \u2014 512\u00d7 GH200 (~74 TB HBM3e), CUDA stack, non-blocking InfiniBand, liquid-cooled. Run simulation and frontier AI on-prem. Make-in-India, GST invoice. 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