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Orchestrating the Next Generation of AI Infrastructure

Modern AI environments require real-time adaptability. Corespan Composer enables orchestration across composable resources, improving efficiency, scalability, and performance for AI and HPC workloads.

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GPU Utilization Challenges: Why AI Infrastructure Is Inefficient

Despite soaring demand for GPUs, many AI environments fail to use them efficiently. Static infrastructure, fragmented resources, and operational complexity often leave valuable compute power underutilized.

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NVME Scratch Pad Diagram

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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NVME Scratch Pad Diagram

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.

Read more about Disaggregated NVMe Scratch Pad: Breaking the GPU Memory Barrier
Disaggregated GPU Memory Pools

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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