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Wolf, Matt

Publications and source records attributed to Wolf, Matt.

StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment

For a production HPC system where storage devices are shared between multiple applications and managed in a best effort manner, contention is often a major problem leading to some storage devices being more loaded than others and causing a significant reduction in I/O throughput. In this paper, we describe our latest efforts StoreRush to resolve this practical issue at the application level without requiring modification to the file and storage system. The proposed scheme uses a two-level messaging system to harvest idle storage via re-routing I/O requests to a less congested storage location so that write performance is improved while limiting the impact on read by throttling re-routing if deemed too much. An analytical model is derived to guide the setup of optimal throttling factor. The proposed scheme is verified against production applications Pixie3D, XGC1 and QMCPack during production windows, which very well demonstrated the effectiveness (e.g., up to 1.8x improvement in write) and scalability of our approach (up to 131,072 cores).

97 MATHEMATICS AND COMPUTING↗

Framework for Physics Computation

The Georgia Tech team has been working in collaboration with ORNL and Rutgers on improved I/O for petascale fusion codes, specifically, to integrate staging methods into the ADIOS framework. As part of this on-going work, we have released the DataTap server as part of the ADIOS release, and we have been working on improving the ‘in situ’ processing capabilities of the ADIOS framework. In particular, we have been moving forward with a design that adds additional metadata to describe the data layout and structure of data that is being moved for I/O purposes, building on the FFS type system developed in our past research

97 MATHEMATICS AND COMPUTING↗