English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present results from parallelizing the unpacking and clustering steps ofthe raw data from the silicon strip modules for reconstruction of chargedparticle tracks. Throughput is further improved by concurrently processingmultiple events using nested OpenMP parallelism on CPU or CUDA streams on GPU.The new implementation along with earlier work in developing a parallelized andvectorized implementation of the combinatoric Kalman filter algorithm hasenabled efficient global reconstruction of the entire event on modern computerarchitectures. We demonstrate the performance of the new implementation onIntel Xeon and NVIDIA GPU architectures.

Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs