People are increasingly concerned about how tectonic processes affect climate and vice versa. We establish a cross-sphere modeling system for volcanic eruptions and atmosphere circulation on a new Sunway supercomputer with a spatial resolution from 10m locally to 3km globally, using an improved multimedium and multiphase smoothed particle hydrodynamics (SPH) combined with a fully coupled meteorology-chemistry global atmospheric modeling scheme. We achieve 400 billion particles and 80% parallel efficiency using 39,000,000 processor cores. The simulation captures the whole dynamic process of the Tonga eruption from shock waves, earthquakes, tsunamis, mushroom clouds to the following 6--7 days of transport and diffusion of ash and water vapor, and preliminarily obtains the influence effect of full coupling of volcano, earthquake, ocean and atmosphere. This work is of great significance for deeply understanding the interaction between tectonic processes and climate change, and establishing an early warning simulation system for similar global hazard events.

With the continuous improvement of supercomputer performance and the integration of artificial intelligence with traditional scientific computing, the scale of applications is gradually increasing, from millions to tens of millions of computing cores, which raises great challenges to achieve high scalability and efficiency of parallel applications on super-large-scale systems. Taking the Sunway exascale prototype system as an example, in this paper we first analyze the challenges of high scalability and high efficiency for parallel applications in the exascale era. To overcome these challenges, the optimization technologies used in the parallel supporting environment software on the Sunway exascale prototype system are highlighted, including the parallel operating system, input/output (I/O) optimization technology, ultra-large-scale parallel debugging technology, 10-million-core parallel algorithm, and mixed-precision method. Parallel operating systems and I/O optimization technology mainly support large-scale system scaling, while the ultra-large-scale parallel debugging technology, 10-million-core parallel algorithm, and mixed-precision method mainly enhance the efficiency of large-scale applications. Finally, the contributions to various applications running on the Sunway exascale prototype system are introduced, verifying the effectiveness of the parallel supporting environment design.

Most supercomputers adopt a data forwarding architecture to achieve storage scalability. However, it results in a significant reduction in single-process bandwidth compared to direct file system access. Moreover, considering that a majority of applications uses only a single process for writing and reading data, the low single-process performance also leads to a time overhead for these applications. This paper proposes an userspace forwarding mechanism DFBUFFER with two performance optimization methods: user-space multi-thread request processing and data write buffer in a unit of file. The client of DFBUFFER is embedded in the application as a library reducing the software overhead, and the server implements multi-thread I/O request processing to improve bandwidth efficiency. The data write buffer can asynchronously handle write requests, which accelerates the write bandwidth of compute nodes. We evaluate DFBUFFER on the Sunway exascale prototype system. The results indicate that in the regular mode of DFBUFFER, both the write and read latency are reduced, and the write bandwidth and large-block read bandwidth of single-process are increased by 1.8 times and 2.8 times respectively. The DFBUFFER buffer mode increases the write bandwidth of a single process by 0.8 times over the regular mode. Although the performance advantage of the regular mode of DFBUFFER gradually weakens with the increase of concurrent processes, the DFBUFFER buffer mode has the effect of improving the write bandwidth, the 64-IO-processes application is increased by 0.2 times.