The high-performance computing I/O stack has been complex due to multiple software
layers, the inter-dependencies among these layers, and the different performance tuning …

Emerging workloads such as artificial intelligence, big data analytics and complex multi-step
workflows alongside future exascale applications are anticipated future HPC workloads …

Large-scale applications typically spend a large fraction of their execution time performing
I/O to a parallel storage system. However, with rapid progress in compute and storage …

This paper offers a solution to overcome the complexities of production system I/O
performance monitoring. We present Beacon, an end-to-end I/O resource monitoring and …

The processor performance of high performance computing (HPC) systems is increasing at
a much higher rate than storage performance. This imbalance leads to I/O performance …

Modern HPC systems are collecting large amounts of I/O performance data. The massive
volume and heterogeneity of this data, however, have made timely performance of in-depth …

Data services such as search, discovery, and management in scalable distributed
environments have traditionally been decoupled from the underlying file systems, and are …

Data services such as search, discovery, and management in scalable distributed
environments have traditionally been decoupled from the underlying file systems, and are …

The system architecture of contemporary supercomputers is growing increasingly intricate
with the ongoing evolution of system-wide network and storage technologies, making it …

With the increase of the scale and intensity of the parallel I/O workloads generated by those
scientific applications running on high performance computing facilities, understanding the …