The Global Computing Lab (GCLab), headed by Dr. Michela Taufer, focuses on various aspects of high performance computing (HPC) and its application to the sciences. We are engaged in the design and testing of efficient computational algorithms and adaptive scheduling policies for scientific computing on GPUs, cloud computing, and volunteer computing. Interdisciplinary research with scientists and engineers in fields such as chemistry and chemical engineering, pharmaceutical sciences, seismology, and mathemat
PRIONN automates prediction of per-job runtime and IO resource usage, enabling IO-aware scheduling on HPC systems. The novelty of our tool is the input of whole job scripts into deep learning models that allow complete automation of runtime and IO resource predictions. We demonstrate the power of PRIONN with runtime and IO resource predictions applied to IO-aware scheduling for real HPC data.
Paper Abstract