Application Performance Analysis: A Report on the Impact of Memory Bandwidth.

As High-Performance Computing (HPC) applications involving massive data sets, including large-scale simulations, data analytics, and machine learning, continue to grow in importance, memory bandwidth has emerged as a critical performance factor in contemporary HPC systems. The rapidly escalating memory performance requirements, which traditional DRAM memories often fail to satisfy, necessitate the use of High-Bandwidth Memory (HBM), which offers high bandwidth, low power consumption, and high integration capacity, making it a promising solution for next-generation platforms. However, despite the notable increase in memory bandwidth on modern systems, no prior work has comprehensively assessed the memory bandwidth requirements of a diverse set of HPC applications and provided sufficient justification for the cost of HBM with potential performance gain. This work presents a performance analysis of a diverse range of scientific applications as well as standard benchmarks on platforms with varying memory bandwidth. The study shows that while the performance improvement of scientific applications varies quite a bit, some applications in CFD, Earth Science, and Physics show significant performance gains with HBM. Furthermore, a cost-effectiveness analysis suggests that the applications exhibiting at least a 30% speedup on the HBM platform would justify the additional cost of the HBM.