Titlebook: Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI; 17th Smoky Mountains Jeffrey Nichols,Becky

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Improving the Performance of the GMRES Method Using Mixed-Precision Techniquesram-Schmidt (MGS) and Classical Gram-Schmidt with Re-orthogonalization (CGSR). Furthermore, our mixed-precision GMRES, when restarted at least once, performed 19% and 24% faster on average than double-precision GMRES for MGS and CGSR, respectively. Our implementation uses generic programming techniq

小丑

On the Use of BLAS Libraries in Modern Scientific Codes at Scaleave additionally traced the training stage of the Convolutional Neural Network (CNN), AlexNet [.]. HPLinpack is also included as a reference, as it exhibits a well-understood BLAS usage pattern. Results from across all the codes show that, unlike HPLinpack, BLAS usage is never more than 25% of the t

CANE

A Systemic Approach to Facilitating Reproducibility via Federated, End-to-End Data Managemente integrated into analytics platforms to easily, correctly, and reliably work with datasets to improve reproducibility of such workloads. We believe that this system can significantly alleviate the burden of data management and improve compliance with the Findable Accessible Interoperable, Reusable

護(hù)身符

Fulfilling the Promises of Lossy Compression for Scientific Applicationsand accuracy, and current generic monolithic compressors are not responding well to this need for specialization. This situation calls for more research and development on the lossy compression technologies. This paper addresses the most pressing research needs regarding the application of lossy com

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DataStates: Towards Lightweight Data Models for Deep Learning metadata that expresses attributes and persistency/movement semantics. A high-performance runtime is the responsible to interpret the metadata and perform the necessary actions in the background, while offering a rich interface to find data states of interest. Using this approach has benefits at se

orthopedist

Scalable Data-Intensive Geocomputation: A Design for Real-Time Continental Flood Inundation Mappingntify and eliminate computational bottlenecks that arise in a geocomputation workflow. Indeed, poor scalability at any of the workflow components is detrimental to the entire end-to-end pipeline. Here, we study a large geocomputation use case in flood inundation mapping that handles multiple nationa

Gesture

Enabling Scientific Discovery at Next-Generation Light Sources with Advanced AI and HPCs will generate in the exabyte (EB) range of data, require tens to 1,000 PFLOPS of peak on-demand computing resources, and utilize billions of core hours per year. Scientific discovery on this scale will be enabled by data management and workflow tools that integrate user facility instruments with s

補(bǔ)助

Visualization as a Service for Scientific Datae interoperability for intelligent scheduling of workflow systems. This work results from a codesign process over analysis, visualization, and workflow tools to provide the flexibility required for production use. Finally, this paper describes a forward-looking research and development plan that cen

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