Large scale simulation performance is dependent on a number of components, however the task of investigation and optimization has long favored computational and communication elements above I/O. Manually extracting the pattern of I/O behavior from a parent application is a useful way of working to address performance issues on a per-application basis, but developing workflows with some degree of automation and flexibility provides a more powerful approach to tackling current and future I/O challenges. In this paper we describe a workload replication workflow that extracts the I/O pattern of an application and recreates its behavior with a flexible proxy application. We demonstrate how simple lightweight characterization can be translated to...
The contemporary parallel I/O software stack is complex due to a large number of configurations for ...
Scientific discovery increasingly depends on complex workflows consisting of multiple phases and som...
Due to the explosive growth in the size of scientific data sets, data-intensive computing is an emer...
Large scale simulation performance is dependent on a number of components, however the task of inves...
Benchmarking and analyzing I/O performance across high performance computing (HPC) platforms is nece...
Designing optimal computer systems for improved performance and energy efficiency requires architect...
Accurate analysis of HPC storage system designs is contin-gent on the use of I/O workloads that are ...
The 2014 TOP500 supercomputer list includes over 40 deployed petascale systems, and the high perform...
High performance computing (HPC) is changing the way science is performed in the 21st Century; exper...
Efficient usage of file systems poses a major challenge for highly scalable parallel applications. T...
As computers and the workloads they run have grown in size and complexity, it has become difficult t...
Abstract—I/O has become one of the determining factors of HPC application performance. Understanding...
Parallel I/O is an essential component of modern High Performance Computing (HPC). Obtaining good I/...
Input/output (I/O) operations can represent a significant proportion of the run-time when large scie...
Adoption of HPC resources presents unique challenges for data-driven workloads at scale. With the in...
The contemporary parallel I/O software stack is complex due to a large number of configurations for ...
Scientific discovery increasingly depends on complex workflows consisting of multiple phases and som...
Due to the explosive growth in the size of scientific data sets, data-intensive computing is an emer...
Large scale simulation performance is dependent on a number of components, however the task of inves...
Benchmarking and analyzing I/O performance across high performance computing (HPC) platforms is nece...
Designing optimal computer systems for improved performance and energy efficiency requires architect...
Accurate analysis of HPC storage system designs is contin-gent on the use of I/O workloads that are ...
The 2014 TOP500 supercomputer list includes over 40 deployed petascale systems, and the high perform...
High performance computing (HPC) is changing the way science is performed in the 21st Century; exper...
Efficient usage of file systems poses a major challenge for highly scalable parallel applications. T...
As computers and the workloads they run have grown in size and complexity, it has become difficult t...
Abstract—I/O has become one of the determining factors of HPC application performance. Understanding...
Parallel I/O is an essential component of modern High Performance Computing (HPC). Obtaining good I/...
Input/output (I/O) operations can represent a significant proportion of the run-time when large scie...
Adoption of HPC resources presents unique challenges for data-driven workloads at scale. With the in...
The contemporary parallel I/O software stack is complex due to a large number of configurations for ...
Scientific discovery increasingly depends on complex workflows consisting of multiple phases and som...
Due to the explosive growth in the size of scientific data sets, data-intensive computing is an emer...