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ERCAP (Energy Research Computing Allocations Process) allocates compute time on NERSC's Perlmutter supercomputer at Lawrence Berkeley National Laboratory, one of the world's largest GPU-based systems with over 7,000 NVIDIA A100 GPUs alongside AMD EPYC CPUs.
ERCAP is the primary mechanism for the broader DOE Office of Science research community (and partner researchers) to access leadership-class GPU resources for AI/ML, foundation model training, scientific AI, climate AI, materials AI, and AI-coupled simulation. Annual allocation cycle: submissions typically open in August and close in early October, with allocations starting January 1 of the following year.
The 2026-cycle ERCAP call closed October 8, 2026 for 2027 allocations. NERSC supports both pre-trained foundation model fine-tuning and pre-training campaigns, with a growing AI/ML user community. Recipients receive both compute hours and consultation from NERSC's NESAP for AI program providing hands-on optimization, MLOps support, and access to advanced features (interactive nodes, Jupyter at scale, ML-optimized storage).
ERCAP complements DOE's INCITE (largest) and ALCC (mission-aligned) allocation pathways.
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Or search similar grants →According to the current listing, eligibility includes: Researchers at U.S. universities, national laboratories, and DOE-affiliated industry whose research is aligned with DOE Office of Science mission areas (energy, materials, biological/environmental, fusion, high-energy physics, nuclear physics, advanced scientific computing). Foreign collaborators eligible through U.S. PIs. Industry researchers eligible for non-proprietary research with broad scientific impact. PIs must have established track record in scientific computing or AI/ML applied to scientific problems. Confirm the full requirements in the official notice before applying.
The current listing shows annual ERCAP allocations on NERSC's Perlmutter supercomputer (7,000+ NVIDIA A100 GPUs + AMD CPUs). Typical AI/ML allocations range from 1,000 to 100,000 GPU node-hours, valued at $50,000 to $5 million USD in compute resources per allocation. Multi-million-hour allocations available for very large AI training campaigns. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NERSC ERCAP Energy Research Computing Allocations on Perlmutter for AI and ML are due October 8, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NERSC ERCAP Energy Research Computing Allocations on Perlmutter for AI and ML is funded by U.S. Department of Energy Office of Science (NERSC at Lawrence Berkeley National Laboratory). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The FY2026 Department of Defense Multidisciplinary University Research Initiative (MURI) program supports basic research in science and engineering at U.S. institutions of higher education, with emphasis on multidisciplinary research where more than one traditional discipline interacts. The Army, Navy, and Air Force basic research offices are seeking applications across 22 topic areas including artificial intelligence and autonomy, information sensing and processing, and systems manipulation. MURI grants typically provide $1.25 million to $1.5 million per year for three years with option to extend two additional years. Approximately $170 million in total funding is available annually across all topics. The program is administered through the Office of Naval Research (ONR), Army Research Office (ARO), and Air Force Office of Scientific Research (AFOSR).
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