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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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ORIENTATION DEPENDENCE OF HYDROGEN ACCELERATED FATIGUE CRACK GROWTH RATES IN PIPELINE STEELS.
Abstract not provided.
Selection of the Accelerating Structure of a Small Linear Electron Accelerator for Radiotherapy
Not provided.
Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication
Writing large amounts of data concurrently to stable storage is a typical I/O pattern of many HPC workflows. This pattern introduces high I/O overheads and results in increased storage space utilization especially for workflows that need to capture the evolution of data structures with high frequency as checkpoints. In this context, many applications, such as graph pattern matching, perform sparse updates to large data structures between checkpoints. For these applications, incremental checkpointing techniques that save only the differences from one checkpoint to another can dramatically reduce the checkpoint sizes, I/O bottlenecks, and storage space utilization. However, such techniques are not without challenges: it is non-trivial to transparently determine what data has changed since a previous checkpoint and assemble the differences in a compact fashion that does not result in excessive metadata. State-of-art data reduction techniques (e.g., compression and de-duplication) have significant limitations when applied to modern HPC applications that leverage GPUs: slow at detecting the differences, generate a large amount of metadata to keep track of the differences, and ignore crucial spatiotemporal checkpoint data redundancy. This paper addresses these challenges by proposing a Merkle tree-based incremental checkpointing method to exploit GPUs' high memory bandwidth and massive parallelism. Experimental results at scale show a significant reduction of the I/O overhead and space utilization of checkpointing compared with state-of-the-art incremental checkpointing and compression techniques.
GPU Acceleration of Spin Tracking in Colliding Beam Accelerators
The RHIC polarized proton program is at the stage of reaching its design goal of polarization, i.e. 70%. A robust and powerful spin tracking program is very critical for the understanding of spin dynamics and helpful in achieving high polarization. Currently, the RHIC spin tracking code is limited by single particle tracking due to the very high computing power. The goal of this project is to greatly improve the spin tracking computing power to explore more beam/machine parameters.
Beams, Accelerator R&D and Future Facilities: Accelerator Frontier Vision [Slides]
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RESEARCH INTO THE EFFECTS OF ANGULAR VELOCITY, ANGULAR ACCELERATION, AND CORIOLIS ACCELERATIONS ON HEALTHY PERSONS AND ON PERSONS WITH DECREASED OR LOST FUNCTION OF THE SEMICIRCULAR CANALS,
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Studies of ion acceleration and neutralization problems using the ion accelerator analysis computer program
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Numerical studies of particle acceleration at turbulent, oblique shocks with an application to prompt ion acceleration during solar flares
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Investigation of the use of a stick force proportional to pitching acceleration for normal-acceleration warning
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An Acceleration Schedule Control for Accelerating a Turbojet Engine and Its Use with a Speed Control
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Accelerator Physics and Technology Research Toward Future Multi-MW Proton Accelerators
Abstract Not Provided
Accelerating Discovery: A Strategic Plan for Accelerator R&D in the U.S.; April 2015
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Towards a Fully Integrated Accelerator on a Chip: Dielectric Laser Acceleration (DLA) From the Source to Relativistic Electrons
Abstract Not Provided
Towards a Fully Integrated Accelerator on a Chip: Dielectric Laser Acceleration (DLA) From the Source to Relativistic Electrons (presentation slides)
Abstract Not Provided