DescriptionAnalysis of scientific simulation data can be concurrently executed with simulation either in time- or space-shared mode. This mitigates the I/O bottleneck. However it results in either stalling the simulation for performing the analysis or transferring data for analysis. In this paper, we improve the throughput of space-shared in situ analysis of large-scale simulations by topology-aware mapping and optimal process decomposition. We propose node interconnect topology-aware process placement for simulation and analysis to reduce the data movement time. We also present an integer linear program for optimal 3D decompositions of simulation and analysis processes. We demonstrate our approach using molecular dynamics simulation on Mira, Cori and Theta supercomputers. Our mapping schemes, combined with optimal 3D process decomposition and code optimizations resulted in up to 30% lower execution times for space-shared in situ analysis than the default approach. Our mappings also reduce MPI collective I/O times by 10-40%.