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All sources NASA NTRS DOE OSTI

DOE OSTI2018

Single-pass parallel prefix scan with dynamic look back

One embodiment of the present invention performs a parallel prefix scan in a single pass that incorporates variable look-back. A parallel processing unit (PPU) subdivides a list of inputs into sequentially-ordered segments and assigns each segment to a streaming multiprocessor (SM) included in the PPU. Notably, the SMs may operate in parallel. Each SM executes write operations on a segment descriptor that includes the status, aggregate, and inclusive-prefix associated with the assigned segment. Further, each SM may execute read operations on segment descriptors associated with other segments. In operation, each SM may perform reduction operations to determine a segment-wide aggregate, may perform look-back operations across multiple preceding segments to determine an exclusive-prefix, and may perform a scan seeded with the exclusive prefix to generate output data. Advantageously, the PPU performs one read operation per input, thereby reducing the time required to execute the prefix scan relative to prior-art parallel implementations.

Merrill, Duane↗

DOE OSTI2016

Parallel Algorithms and Patterns

This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

SU-F-BRB-01: How Effective Is Abdominal Compression at Reducing Lung Motion? An Analysis Using Deformable Image Registration Within Different Sub-Regions of the Lung

Purpose: To investigate the effectiveness of employing abdominal compression (AC) in reducing motion for the target region and sub-regions of the lung as part of the planning process for radiation therapy. Methods: Fourteen patients with early lung cancer were scanned with 4DCT and it was determined that target motion exceeded our institutional limit of > 8 mm motion and received a repeat 4DCT with AC. For each 4DCT, deformable image registration (DIR) was used to map the max inhale to the max exhale phase to determine the deformation vector fields (DVF). DIR was performed with Morphons and Demons algorithms. The mean DVF was used to represent that sub-region for each patient. The magnitudes of the mean DVF were quantified for the target and 12 sub-regions in the AP, LR SI directions. The sub-regions were contoured on each lung as (add prefix R or L for lung): Upper-Anterior (UA), Upper-Posterior (UP), Mid-Anterior (MA), Mid-Posterior (MP), Lower-Anterior (LA) and Lower-Posterior (LP). Results: The min/max SI motion for the target on the uncompressed 4DCT was 8mm/24.5 mm. The magnitude of decrease in SI was greatest in the RLP region (3.7±4.0mm) followed by target region (3.3±2.2mm) and finally the LLP region (3.0±3.5mm). The magnitude of decrease in 3D vector followed the same trend; RLP (3.5±2.2mm) then GTV (3.5±2.6mm) then LLP (2.7±3.8mm). 79% of the cases had a SI decrease of >12.5%, 43% had a SI decrease of >25% and 21% had a SI decrease of >50% as compared to the motion on the uncompressed 4DCT. Conclusion: AC is useful in reducing motion with the largest decreases observed in the lower posterior regions of the lungs. However, it should be noted that AC will not greatly decrease motion for all cases as 21% of cases did not reduce SI motion more than 12.5% of initial motion.

60 APPLIED LIFE SCIENCES↗