Scalable Distributed Tensor Decomposition for Multi-Omics Clinical Phenotyping
High-Performance Asynchronous Factorization on Heterogeneous GPU Clusters
High-throughput multi-omics sequencing generates multi-way tensor arrays exceeding petabyte scales, creating urgent computational bottlenecks for clinical discovery. We introduce Distributed Tucker-CP (DT-CP), an asynchronous lock-free tensor factorization algorithm optimized for CUDA/ROCm memory hierarchies with adaptive communication pipelining. On a 256-node GPU cluster, DT-CP demonstrates a 14.8x acceleration over state-of-the-art MPI-Tensor frameworks, processing 4.2 billion patient feature interactions in 18.4 minutes while maintaining 99.4% spectral accuracy. DT-CP unlocks real-time multi-omics phenotyping in clinical genomics pipelines, providing an open-source mathematical infrastructure for precision medicine.