Co-designing HPC-systems by computing capabilities and management flexibility to accommodate bioinformatic workflows at different complexity levels

摘要

The field of biology is producing data faster than ever before. To approach its analysis efficiently, one can take advantage of a systematic symbiosis between the power of huge distributed-memory systems and the flexibility of locally managed shared-memory servers. Here, we introduce the concept of a "small and smart" High Performance Computing resource as an intermediary between a personal computer and a supercomputer to accommodate complex tasks in biology. Such a supplementary server, specifically designed and configured for a particular purpose, can facilitate efficient and convenient data processing by maximizing shared-memory multi-tasking/threading on CPU/GPU. It seems most reasonable to consider it as a beacon for further co-development of the increasingly common "medium-hard" algorithms/pipelines in life sciences and hardware for shared-memory parallelism. This leaves supercomputers with specifically developed highly parallel implementations of the most resource-demanding operations, to ensure optimal performance amid efficient utilization of expensive infrastructure.