Case Study: LayerJot scales AI training from 5 to 256 GPUs with Strong Compute

LayerJot scales to 256 GPUs in 1 week with Strong Compute

LayerJot, a med-tech startup, faced the challenge of managing complex AI workloads across multiple datasets and models with limited on-premises hardware and high operational overhead. Their compute-intensive research was constrained by slow deployment times and an inability to scale. Strong Compute was engaged to address these infrastructure limitations.

The solution implemented by Strong Compute involved deploying an AI engineer on-site for a week to optimize their infrastructure using the Strong Compute Instant Super Computer. This enabled LayerJot to scale from 5 to 256 GPUs across three cloud providers with zero dev-ops. The results were breakthrough: they ran 44 experiments, achieved 60GB/sec inter-cloud data transfer speeds, and reduced job deployment time from hours to minutes. This partnership resolved complex integration challenges and positioned LayerJot to accelerate its medical technology innovation.

LayerJot