Here we report IceCube’s first experiences of running GPU simulations on the Titan supercomputer. This undertaking was non-trivial because Titan is designed for High Performance Computing (HPC) workloads, whereas IceCube’s workloads fall under the High Throughput Computing (HTC) category. In particular: (i) Titan’s design, policies, and tools are geared heavily toward large MPI applications, while IceCube’s workloads consist of large numbers of relatively small independent jobs, (ii) Titan compute nodes run Cray Linux, which is not directly compatible with IceCube software, and (iii) Titan compute nodes cannot access outside networks, making it impossible to access IceCube’s CVMFS repositories and workload management systems. This report examines our experience of packaging our application in Singularity containers and using HTCondor as the second-level scheduler on the Titan supercomputer.
High-performance computing and Grid applications in high-throughput protein crystallography
