Publications

Lawson, Margaret R.

Abstract not provided.

Lawson, Margaret R.; Lofstead, Gerald F.

Abstract not provided.

Proceedings of PDSW 2019: IEEE/ACM 4th International Parallel Data Systems Workshop - Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis

Monnier, Nolan; Lofstead, Jay; Lawson, Margaret R.; Curry, Matthew J.

This paper explores how we used IO500 and the Mistral tool from Ellexus to observe detailed performance characteristics to inform tuning IO performance on Astra, a ARM-based Sandia machine with an all flash, Lustre-based storage array. Through this case study, we demonstrate that IO500 serves as a meaningful storage benchmark, even for all flash storage. We also demonstrate that using fine-grained profiling tools, such as Mistral, is essential for revealing tuning requirement details. Overall, this paper demonstrates the value of a broad spectrum benchmark, like IO500, together with a fine grained performance analysis tool, such as Mistral, for understanding detailed storage system performance for better informed tuning.

Lofstead, Gerald F.; Ryan, Ashleigh R.; Lawson, Margaret R.

Abstract not provided.

Lawson, Margaret R.; Lofstead, Gerald F.

Abstract not provided.

Lawson, Margaret R.; Lofstead, Gerald F.

Abstract not provided.

Sevilla, Michael A.; Nasirigerdeh, Reza N.; Maltzahn, Carlos M.; LeFevre, Jeff L.; Watkins, Noah W.; Alvaro, Peter A.; Lawson, Margaret R.; Lofstead, Gerald F.; Pivarski, Jim P.

Abstract not provided.

Proceedings of the 9th Workshop on Scientific Cloud Computing, ScienceCloud 2018 - Co-located with HPDC 2018

Ulmer, Craig D.; Mukherjee, Shyamali M.; Templet, Gary J.; Kordenbrock, Todd; Levy, Scott; Lofstead, Jay; Widener, Patrick W.; Lawson, Margaret R.

Composition of computational science applications, whether into ad hoc pipelines for analysis of simulation data or into well-defined and repeatable workflows, is becoming commonplace. In order to scale well as projected system and data sizes increase, developers will have to address a number of looming challenges. Increased contention for parallel filesystem bandwidth, accomodating in situ and ex situ processing, and the advent of decentralized programming models will all complicate application composition for next-generation systems. In this paper, we introduce a set of data services, Faodel, which provide scalable data management for workflows and composed applications. Faodel allows workflow components to directly and efficiently exchange data in semantically appropriate forms, rather than those dictated by the storage hierarchy or programming model in use. We describe the architecture of Faodel and present preliminary performance results demonstrating its potential for scalability in workflow scenarios.

Lawson, Margaret R.

Abstract not provided.

Lawson, Margaret R.; Lawson, Margaret R.; Lawson, Margaret R.

Abstract not provided.

Ulmer, Craig D.; Kordenbrock, Todd H.; Lawson, Margaret R.; Levy, Scott L.; Lofstead, Gerald F.; Mukherjee, Shyamali M.; Sjaardema, Gregory D.; Templet, Gary J.; Ward, Harry L.; Widener, Patrick W.

Abstract not provided.

Lawson, Margaret R.; Lofstead, Gerald F.; Levy, Scott L.; Widener, Patrick W.; Ulmer, Craig D.; Mukherjee, Shyamali M.; Templet, Gary J.; Kordenbrock, Todd H.

Abstract not provided.

Lawson, Margaret R.; Lofstead, Gerald F.; Levy, Scott L.; Widener, Patrick W.; Ulmer, Craig D.; Mukherjee, Shyamali M.; Templet, Gary J.; Kordenbrock, Todd H.

Abstract not provided.

Ulmer, Craig D.; Mukherjee, Shyamali M.; Templet, Gary J.; Levy, Scott L.; Lofstead, Gerald F.; Widener, Patrick W.; Kordenbrock, Todd H.; Lawson, Margaret R.

Abstract not provided.