Resources
Disaggregated NVMe Scratch Pad: Breaking the GPU Memory Barrier
Corespan’s disaggregated NVMe scratch pad creates a shared, high-performance storage tier that extends GPU memory, enabling scalable AI workloads with better utilization and predictable performance.
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Disaggregated GPU Memory Pools
Past 8 GPUs, network hops stall syncs and strand vRAM. Corespan disaggregates GPU memory into one photonic PCIe pool, so hosts draw needed capacity on demand—higher utilization, lower cost, at scale.
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AI’s Second Wave: From Training Hype to Inference Reality
AI’s second wave shifts from model training to inference efficiency—optimizing cost-per-token and energy use. Dynamic, composable GPU fabrics unlock stranded capacity and maximize utilization.
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Democratize AI Infrastructure for the Oil, Gas and Energy Industry
AI initiatives in energy often stall when transitioning from pilot to production due to infrastructure inefficiencies, data fragmentation, and GPU underutilization.
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