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Riley, Daniel

Publications and source records attributed to Riley, Daniel.

49 records · Page 3
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DOE OSTI2019

Multi-Threaded Output in CMS using ROOT

CMS has worked aggressively to make use of multi-core architectures, routinely running 4- to 8-core production jobs in 2017. The primary impediment to efficiently scaling beyond 8 cores has been our ROOT-based output module, which has been necessarily single threaded. In this paper we explore the changes made to the CMS framework and our ROOT output module to overcome the previous scaling limits, using two new ROOT features: the \texttt{TBufferMerger} asynchronous file merger, and Implicit Multi-Threading. We examine the architecture of the new parallel output module, the specific accommodations and modifications that were made to ensure compatibility with the CMS framework scheduler, and the performance characteristics of the new output module.

Riley, Daniel↗
DOE OSTI2018

Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events

The High-Luminosity Large Hadron Collider at CERN will be characterized by greater pileup of events and higher occupancy, making the track reconstruction even more computationally demanding. Existing algorithms at the LHC are based on Kalman filter techniques with proven excellent physics performance under a variety of conditions. Starting in 2014, we have been developing Kalman-filter-based methods for track finding and fitting adapted for many-core SIMD processors that are becoming dominant in high-performance systems. This paper summarizes the latest extensions to our software that allow it to run on the realistic CMS-2017 tracker geometry using CMSSW-generated events, including pileup. The reconstructed tracks can be validated against either the CMSSW simulation that generated the hits, or the CMSSW reconstruction of the tracks. In general, the code's computational performance has continued to improve while the above capabilities were being added. We demonstrate that the present Kalman filter implementation is able to reconstruct events with comparable physics performance to CMSSW, while providing generally better computational performance. Further plans for advancing the software are discussed.

Cerati, Giuseppe↗
DOE OSTI2018

A Performance Model for Bifacial PV Modules

Sandia National Laboratories, the National Renewable Energy Laboratory, and the University of Iowa are collaborating to develop a performance model for bifacial PV modules. As with monofacial PV modules, a bifacial PV model consists of sequential operation of the component sub-models. Bifacial PV modules accept light on both their front and rear surfaces which presents a unique modeling challenge. This paper describes the approach of Sandia, NREL, and the University of Iowa to create a bifacial PV model and verify its accuracy with measured field data.

14 SOLAR ENERGY↗
DOE OSTI2018

A Practical Irradiance Model for Bifacial PV Modules

A model, suitable for a row or multiple rows of photovoltaic (PV) modules, is presented for estimating the backside irradiance for bifacial PV modules. The model, which includes the effects of shading by the PV rows, is based on the use of configuration factors to determine the fraction of a source of irradiance that is received by the backside of the PV module. Backside irradiances are modeled along the sloped height of the PV module, but assumed not to vary along the length of the PV row. The backside irradiances are corrected for angle-ofincidence losses and may be added to the front side irradiance to determine the total irradiance resource for the PV cell. Model results are compared with the measured backside irradiances for NREL and Sandia PV systems, and with results when using ray tracing software.

14 SOLAR ENERGY↗
DOE OSTI2018

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗