{
  "name": "NAIRR Pilot Computing Systems and Accelerator Specifications",
  "description": "Comparative technical specifications of high-performance supercomputers, AI accelerators, and cloud platforms available through the National AI Research Resource (NAIRR) Pilot allocation tracks, compiled from official facility documentation and partner portals.",
  "page": "https://casrai.org/guides/nairr-pilot",
  "publisher": "CASRAI",
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "dateModified": "2026-11-15T00:42:35Z",
  "temporalCoverage": "2024/2026",
  "spatialCoverage": "United States",
  "columns": [
    {
      "name": "System / Platform",
      "unit": "",
      "description": "Name of the supercomputing cluster or cloud infrastructure"
    },
    {
      "name": "Operating Facility",
      "unit": "",
      "description": "Host institution or federal leadership laboratory"
    },
    {
      "name": "Primary AI Accelerators",
      "unit": "",
      "description": "Type and generation of GPU or specialized AI processor"
    },
    {
      "name": "Aggregate System Memory",
      "unit": "TB",
      "description": "Total available host system memory across compute nodes"
    },
    {
      "name": "Peak AI Performance",
      "unit": "PFLOPS",
      "description": "Theoretical peak half-precision or tensor performance"
    },
    {
      "name": "Allocation Mechanism",
      "unit": "",
      "description": "Primary proposal submission route and award duration"
    },
    {
      "name": "Primary Research Suitability",
      "unit": "",
      "description": "Recommended scientific machine learning and AI workload types"
    }
  ],
  "rows": [
    {
      "System / Platform": "Delta / DeltaAI",
      "Operating Facility": "NCSA (UIUC)",
      "Primary AI Accelerators": "NVIDIA H100 and A100 Tensor Core GPUs",
      "Aggregate System Memory": 120,
      "Peak AI Performance": 180,
      "Allocation Mechanism": "NAIRR Research / ACCESS (12 mo)",
      "Primary Research Suitability": "Deep learning pretraining, vision transformers, multi-GPU scaling"
    },
    {
      "System / Platform": "Bridges-2",
      "Operating Facility": "PSC (Carnegie Mellon / Pitt)",
      "Primary AI Accelerators": "NVIDIA A100 (40GB/80GB) and V100",
      "Aggregate System Memory": 192,
      "Peak AI Performance": 15,
      "Allocation Mechanism": "NAIRR Research / ACCESS (12 mo)",
      "Primary Research Suitability": "Foundation model fine-tuning, large-memory graph AI, NLP"
    },
    {
      "System / Platform": "Perlmutter",
      "Operating Facility": "NERSC (DOE)",
      "Primary AI Accelerators": "6,000+ NVIDIA A100 Tensor Core GPUs",
      "Aggregate System Memory": 480,
      "Peak AI Performance": 100,
      "Allocation Mechanism": "NAIRR Research / DOE Track (12 mo)",
      "Primary Research Suitability": "Scientific AI, climate simulation, molecular dynamics, physics-ML"
    },
    {
      "System / Platform": "Polaris",
      "Operating Facility": "ALCF (DOE)",
      "Primary AI Accelerators": "2,240 NVIDIA A100 GPUs (560 nodes)",
      "Aggregate System Memory": 280,
      "Peak AI Performance": 44,
      "Allocation Mechanism": "NAIRR Secure / DOE Track (12 mo)",
      "Primary Research Suitability": "Foundation model training, privacy-preserving AI, neural operators"
    },
    {
      "System / Platform": "Anvil",
      "Operating Facility": "Purdue University",
      "Primary AI Accelerators": "NVIDIA A100 Tensor Core GPUs",
      "Aggregate System Memory": 100,
      "Peak AI Performance": 8,
      "Allocation Mechanism": "NAIRR Classroom / ACCESS (3-6 mo)",
      "Primary Research Suitability": "Academic instruction, student AI labs, exploratory machine learning"
    },
    {
      "System / Platform": "Expanse",
      "Operating Facility": "SDSC (UC San Diego)",
      "Primary AI Accelerators": "NVIDIA V100 and A100 GPU nodes",
      "Aggregate System Memory": 96,
      "Peak AI Performance": 6,
      "Allocation Mechanism": "NAIRR Research / ACCESS (12 mo)",
      "Primary Research Suitability": "Composable scientific workflows, bioinformatics AI, multimodal tasks"
    },
    {
      "System / Platform": "Jetstream2",
      "Operating Facility": "Indiana University",
      "Primary AI Accelerators": "NVIDIA A100 and virtualized GPU slices",
      "Aggregate System Memory": 64,
      "Peak AI Performance": 4,
      "Allocation Mechanism": "NAIRR Classroom / Research (6-12 mo)",
      "Primary Research Suitability": "Interactive JupyterHub notebooks, containerized AI development"
    },
    {
      "System / Platform": "Cerebras CS-2/CS-3",
      "Operating Facility": "Cerebras Systems / PSC",
      "Primary AI Accelerators": "Wafer-Scale Engine (850,000 AI cores)",
      "Aggregate System Memory": 40,
      "Peak AI Performance": 150,
      "Allocation Mechanism": "NAIRR Advanced Accelerator Track",
      "Primary Research Suitability": "Extreme-scale LLM training, genomics, structural biology modeling"
    }
  ],
  "sources": [
    {
      "title": "NAIRR Pilot Resource Catalog",
      "url": "https://nairrpilot.org/resources",
      "accessed": "2026-11-14"
    },
    {
      "title": "NCSA Delta & DeltaAI Architecture",
      "url": "https://access-ci.org",
      "accessed": "2026-11-14"
    },
    {
      "title": "ALCF Polaris System Overview",
      "url": "https://www.alcf.anl.gov",
      "accessed": "2026-11-14"
    },
    {
      "title": "NERSC Perlmutter Documentation",
      "url": "https://www.nersc.gov",
      "accessed": "2026-11-14"
    }
  ]
}