3rd Workshop on E-science ReseaRch leading tO negative Results
Tuesday, Oct 10, 2023 at 14:00, MEGARON A
ERROR 2023 provides the e-Science community a dedicated and active forum for exchanging cross-discipline experiences on research leading to negative results and lessons learned. The workshop covers both applications and systems areas, including topics in research methodology, reproducibility, the applications/systems interface, social problems in computational science, and other relevant areas. Zoom link: https://www.zoomgov.com/j/1604968445?pwd=c1NaT1o5S01yK0xEMnlwbmNQMDl2Zz09
Info about past ERROR workshop may be found here.
In conjunction withTime | Event | |
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2:00-2:05pm | Welcome & Introduction Ketan Maheshwari |
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2:05-2:30pm | Negative Results in Cloud, Edge and HPC Science Beth Plale, Indiana University Bloomington |
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2:30pm-2:40pm | Scientific data reduction: benefits and lessons learned Qian Gong, Oak Ridge National Laboratory |
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2:40pm-2:50pm | Lessons learned from developing Automated Machine Learning on HPC Romaine Egele, Université Paris-Saclay |
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2:50pm-3:00pm | Human error: reference out of scope Adam Craig, Hong Kong Baptist University |
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3:00pm-3:10pm | Opportunities and Challenges in Real-world System Deployments Keshav Kaushik, Birla Institute Of Technology And Science at Pilani |
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3:10pm-3:20pm | When the not-so-smart manipulation of smart pointers kills performance Fred Suter, Oak Ridge National Laboratory |
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3:20pm-3:30pm | Benchmarking the Bruck Algorithm for All-to-All Communication in multi-GPU environment using NCCL Andres Sewell, Utah State University |
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3:30pm-4:00pm | Break ☕ |
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4:00pm-5:00pm | Discussion Lead By Daniel S. Katz |
All deadlines are Anywhere on Earth (AoE).
Escience researchers often invest significant time and effort in projects that can have unexpected outcomes. When results are obtained that do not fit the established molds expected by publishing venues, these results can be lost. The ERROR Workshop invites research results from computing and computational projects that encounter unexpected or negative results that would be difficult to report on elsewhere.
Novel hardware technologies and machine learning approaches (among others) are rapidly changing approaches, methods, and scale applied in escience domains. Researchers must deal with this novelty in multiple dimensions, many of which are beyond their control. Consequently, it is likely that some of the obtained results will not be of the expected form: they are negative (deviating from initial hypothesis), abnormal (anomalous to results from similar studies), or otherwise not useful in the established sense.
Under normal circumstances, such negative results and why they were obtained are seldom discussed, analyzed and published. Useful lessons are thus lost to the scientific community. Yet ignoring such results and the process by which they were obtained poses a risk of repetition. The fact that other researchers likely face the same situations and the same pitfalls further increases the cost of research, a cost that would have been avoided if the negative results were brought forward and discussed in-depth within and across communities.
Accepted papers from the workshop will be published as part of eScience 2023 proceedings to be published by the IEEE Computer Society Press, USA and made available online through the IEEE Digital Library.
Authors are invited to submit a maximum of 6-page manuscripts describing
original and unpublished work surrounding the aforementioned topics. The format
of the paper should be of double column text using single spaced 10 point size
on 8.5 x 11 inch pages, as per IEEE 8.5 x 11 manuscript guidelines. Templates
are available from
this link.
Authors should submit a PDF file that will print on a postscript printer
to the easychair conference
system.
Oak Ridge National Laboratory, USA
Argonne National Laboratory, USA
University of Illinois at Urbana-Champaign, USA
University of Southern California, USA
CNRS, France
Humboldt-Universitaet zu Berlin, Germany
University of Southern California, USA
DePaul University, USA
Barcelona Supercomputing Center, Spain
Oak Ridge National Laboratory, USA
Oak Ridge National Laboratory, USA
University of Minho, Portugal
Oak Ridge National Laboratory, USA