Jay Lofstead
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View article: Report on Challenges of Practical Reproducibility for Systems and HPC Computer Science
Report on Challenges of Practical Reproducibility for Systems and HPC Computer Science Open
This report from the NSF-sponsored REPETO project synthesizes findings from the November 2024 Community Workshop on Practical Reproducibility in HPC, which convened researchers, artifact authors, reviewers, and chairs of reproducibility in…
View article: Performance Models for a Two-tiered Storage System
Performance Models for a Two-tiered Storage System Open
This work describes the design, implementation and performance analysis of a distributed two-tiered storage software. The first tier functions as a distributed software cache implemented using solid-state devices~(NVMes) and the second tie…
View article: To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation
To Derive or Not to Derive: I/O Libraries Take Charge of Derived Quantities Computation Open
The ever-increasing volume of data produced by HPC simulations necessitates scalable methods for data exploration and knowledge extraction. Scientific data analysis often involves complex queries across distributed datasets, requiring mani…
View article: Shaping the Future of Self-Driving Autonomous Laboratories Workshop
Shaping the Future of Self-Driving Autonomous Laboratories Workshop Open
The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific …
View article: Proceedings of the 36th International Conference on Scientific and Statistical Database Management
Proceedings of the 36th International Conference on Scientific and Statistical Database Management Open
International audience
View article: Complete and Correct Transfer of Information (CACTI)
Complete and Correct Transfer of Information (CACTI) Open
Many distributed systems, file transfer mechanisms, and message passing systems offer reliability mechanisms such as acknowledgements, retries, and durability. While these tools may be “good enough” for their typical use cases, they may no…
View article: Challenges and Strategies for Testing Automation Practices at Sandia National Laboratories
Challenges and Strategies for Testing Automation Practices at Sandia National Laboratories Open
Sandia National Laboratories is a premier United States national security laboratory which develops science-based technologies in areas such as nuclear deterrence, energy pro- duction, and climate change. Computing plays a key role in its …
View article: NSDF-Services: Integrating Networking, Storage, and Computing Services into a Testbed for Democratization of Data Delivery
NSDF-Services: Integrating Networking, Storage, and Computing Services into a Testbed for Democratization of Data Delivery Open
The lack of a readily accessible, tightly integrated data fabric connecting high-speed networking, storage, and computing services remains a critical barrier to the democratization of scientific discovery. To address this challenge, we are…
View article: Message from the Program Committee Chairs
Message from the Program Committee Chairs Open
Welcome to the 35th IEEE International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2023, in Porto Alegre, Brazil. The conference is sponsored by the Brazilian Computer Society (SBC) and the IEEE Computer Soc…
View article: Towards a More Effective Hybrid Workforce Culture in a Computationally Focused Research Center
Towards a More Effective Hybrid Workforce Culture in a Computationally Focused Research Center Open
It is essential to Sandia National Laboratory’s continued success in scientific and technological advances and mission delivery to embrace a hybrid workforce culture under which current and future employees can thrive. This report focuses …
View article: Data Pallets: Containerizing Storage For Reproducibility and Traceability.
Data Pallets: Containerizing Storage For Reproducibility and Traceability. Open
Trusting simulation output is crucial for Sandia’s mission objectives. Here, we rely on these simulations to perform our high-consequence mission tasks given national treaty obligations. Other science and modeling applications, while they …
View article: An Evaluation of DAOS for Simulation and Deep Learning HPC Workloads
An Evaluation of DAOS for Simulation and Deep Learning HPC Workloads Open
Traditionally, distributed storage systems have relied upon the interfaces provided by OS kernels to interact with storage hardware. However, much research has shown that OSes impose serious overheads on every I/O operation, especially on …
View article: Metadata Management to Aid Data Discovery
Metadata Management to Aid Data Discovery Open
Metadata Management to Aid Data Discovery
View article: Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use Case
Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use Case Open
Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use Case
View article: Building Trust in Earth Science Findings through Data Traceability and Results Explainability
Building Trust in Earth Science Findings through Data Traceability and Results Explainability Open
To trust findings in computational science, scientists need workflows that trace the data provenance and support results explainability. As workflows become more complex, tracing data provenance and explaining results become harder to achi…
View article: Failure Sources in Machine Learning for Medicine—A Study
Failure Sources in Machine Learning for Medicine—A Study Open
Machine learning (ML) inherently suffers from at least a small amount of inaccuracy. Typically, these errors are acceptable in trade for either speed to an answer or the ability to find an answer at all. For high consequence domains, such …
View article: Managing Randomness to Enable Reproducible Machine Learning
Managing Randomness to Enable Reproducible Machine Learning Open
The National Information Standards Organization defines scientific reproducibility as "obtaining consistent results using the same input data, computational steps, methods, and code, and conditions of analysis'' [12] reproducibility. Repro…
View article: IO500 ISC 22 list
IO500 ISC 22 list Open
All of the data associated with the IO500 ISC 2022 list
View article: IO500 ISC 22 list
IO500 ISC 22 list Open
All of the data associated with the IO500 ISC 2022 list