A. Yagil
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View article: Line Segment Tracking in the High-luminosity LHC
Line Segment Tracking in the High-luminosity LHC Open
The Large Hadron Collider (LHC) will be upgraded to Highluminosity LHC, increasing the number of simultaneous proton-proton collisions (pileup, PU) by several-folds. The harsher PU conditions lead to exponentially increasing combinatorics …
View article: Speeding up the CMS track reconstruction with a parallelized and vectorized Kalman-filter-based algorithm during the LHC Run 3
Speeding up the CMS track reconstruction with a parallelized and vectorized Kalman-filter-based algorithm during the LHC Run 3 Open
One of the most challenging computational problems in the Run 3 of the Large Hadron Collider (LHC) and more so in the High-Luminosity LHC (HL-LHC) is expected to be finding and fitting charged-particle tracks during event reconstruction. T…
View article: Segment Linking: A Highly Parallelizable Track Reconstruction Algorithm for HL-LHC
Segment Linking: A Highly Parallelizable Track Reconstruction Algorithm for HL-LHC Open
The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) will produce particle collisions with up to 200 simultaneous proton-proton interactions. These unprecedented conditions will create a combinatorial complexity for charged-pa…
View article: Segment Linking: A Highly Parallelizable Track Reconstruction Algorithm for HL-LHC
Segment Linking: A Highly Parallelizable Track Reconstruction Algorithm for HL-LHC Open
The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) will produce particle collisions with up to 200 simultaneous proton-proton interactions. These unprecedented conditions will create a combinatorial complexity for charged-pa…
View article: Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs
Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs Open
We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is further improved by concurrently processing multiple event…
View article: Parallelization for HEP Reconstruction
Parallelization for HEP Reconstruction Open
in porting existing serial algorithms to many-core devices. Measurements of both data processing and data transfer latency are shown, considering different I/O strategies to/from the parallel devices.
View article: Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm
Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm Open
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filter…
View article: Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm
Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm Open
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filter…
View article: Kalman filter tracking on parallel architectures
Kalman filter tracking on parallel architectures Open
\nPower density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGPU, ARM and Intel MIC. In order to achieve the theoretical…