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Feng, Wu-chun

Publications and source records attributed to Feng, Wu-chun.

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

ExaFEL: extreme-scale real-time data processing for X-ray free electron laser science

ExaFEL is an HPC-capable X-ray Free Electron Laser (XFEL) data analysis software suite for both Serial Femtosecond Crystallography (SFX) and Single Particle Imaging (SPI) developed in collaboration with the Linac Coherent Lightsource (LCLS), Lawrence Berkeley National Laboratory (LBNL) and Los Alamos National Laboratory. ExaFEL supports real-time data analysis via a cross-facility workflow spanning LCLS and HPC centers such as NERSC and OLCF. Our work therefore constitutes initial path-finding for the US Department of Energy's (DOE) Integrated Research Infrastructure (IRI) program. We present the ExaFEL team's 7 years of experience in developing real-time XFEL data analysis software for the DOE's exascale supercomputers. We present our experiences and lessons learned with the Perlmutter and Frontier supercomputers. Furthermore we outline essential data center services (and the implications for institutional policy) required for real-time data analysis. Finally we summarize our software and performance engineering approaches and our experiences with NERSC's Perlmutter and OLCF's Frontier systems. This work is intended to be a practical blueprint for similar efforts in integrating exascale compute resources into other cross-facility workflows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Optimizing the Energy Usage and Cognitive Value of Extreme-Scale Data-Analysis Approaches

This report serves as a record that we have successfully completed work on the proposal Optimizing the Energy Usage and Cognitive Value of Extreme Scale Analysis Approaches, or, more succinctly, ECX. This includes successful completion of all three phases of the project, findings as summarized below, strong publications across the fields represented in the proposal, and a set of artifacts (code, websites, and other documentation) available to the public. In total, the results of this project represent significant findings in each domain, and a toolkit that will allow the community to engage with this work, advancing it and contributing to it in the years ahead. They also form the basis for a successfully funded follow-on project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Optimizing 10-Gigabit Ethernet for Networks of Workstations, Clusters, and Grids: A Case Study

Here, this paper presents a case study of the 10-Gigabit Ethernet (10GbE) adapter from Intel R . Specifically, with appropriate optimizations to the configurations of the 10GbE adapter and TCP, we demonstrate that the 10GbE adapter can perform well in local-area, storage-area, system-area, and wide-area networks. For local-area, storage-area, and system-area networks in support of networks of workstations, network-attached storage, and clusters, respectively, we can achieve over 7-Gb/s end-to-end throughput and 12-µs end-to-end latency between applications running on Linux-based PCs. For the wide-area network in support of grids, we broke the recently-set Internet2 Land Speed Record by 2.5 times by sustaining an end-to-end TCP/IP throughput of 2.38 Gb/s between Sunnyvale, California and Geneva, Switzerland (i.e., 10,037 kilometers) to move over a terabyte of data in less than an hour. Thus, the above results indicate that 10GbE may be a cost-effective solution across a multitude of computing environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Optimizing the Energy Usage and Cognitive Value of Extreme-Scale Data-Analysis Approaches (Final Report)

This report serves as a record that we have successfully completed work on the proposal Optimizing the Energy Usage and Cognitive Value of Extreme Scale Analysis Approaches, or, more succinctly, ECX. This includes successful completion of all three phases of the project, findings as summarized below, strong publications across the fields represented in the proposal, and a set of artifacts (code, websites, and other documentation) available to the public. In total, the results of this project represent significant findings in each domain, and a toolkit that will allow the community to engage with this work, advancing it and contributing to it in the years ahead. They also form the basis for a successfully funded follow-on project. This executive summary presents findings, tools and publications resulting from the ECX project. The balance of the report then provides more detail on these results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

CoreTSAR: Core Task-Size Adapting Runtime

Heterogeneity continues to increase at all levels of computing, with the rise of accelerators such as GPUs, FPGAs, and other co-processors into everything from desktops to supercomputers. As a consequence, efficiently managing such disparate resources has become increasingly complex. CoreTSAR seeks to reduce this complexity by adaptively worksharing parallel-loop regions across compute resources without requiring any transformation of the code within the loop. Lastly, our results show performance improvements of up to three-fold over a current state-of-the-art heterogeneous task scheduler as well as linear performance scaling from a single GPU to four GPUs for many codes. In addition, CoreTSAR demonstrates a robust ability to adapt to both a variety of workloads and underlying system configurations.

97 MATHEMATICS AND COMPUTING↗