Abstract
This project will design and develop high-performance computational frameworks which will enable effective analysis of omics data produced from mass spectrometry machines. The proposed high-performance computing (HPC) techniques will enable identification of novel peptides/proteins, and insights into microbiome communities and their effects on human health, agriculture, and environments.
The project will focus on the design and development of: (1) CPU-GPU based method for processing of large-scale MS-based omics with communication-avoiding parallel pipelines; (2) methods for exploiting multiple GPUs on single node which is extended to memory-distributed CPU-GPU nodes on supercomputing machines; (3) hardware/software co-designs using CPU-FPGA architectures. This computational infrastructure will allow scientists to use large heterogeneous supercomputers, and the development of hardware/software designs will enable us to incorporate semiconductor designs directly on mass spectrometry machines. The development of such semiconductors designed for end-use application (of MS omics data) will preserve US global economic competitiveness, and will accelerate urgently needed personalized nutrition studies, human gut microbiome research, and cancer therapeutics studies.
Methods
Method development for this work is ongoing.