28 research outputs found
Improving tracking algorithms with machine learning a case for line-segment tracking at the High Luminosity LHC
No full textIn this work, we present a study on ways that tracking algorithms can be improved with machine learning (ML). We base this study on a line-segment-based tracking (LST) algorithm that we have designed to be naturally parallelized and vectorized in order to efficiently run on modern processors. LST has been developed specifically for the Compact Muon Solenoid (CMS) Experiment at the LHC, towards the High Luminosity LHC (HL-LHC) upgrade. Moreover, we have already shown excellent efficiency and performance results as we iteratively improve LST, leveraging a full simulation of the CMS detector. At the same time, promising deep-learning-based tracking algorithms, such as Graph Neural Networks (GNNs), are being pioneered on the simplified TrackML dataset. These results suggest that parts of LST could be improved or replaced by ML. Thus, a thorough, step-by-step investigation of exactly how and where ML can be utilized, while still meeting realistic HL-LHC performance and efficiency constraints, is implemented as follows. First, a lightweight neural network is used to replace and improve upon explicitly defined track quality selections. This neural network is shown to be highly efficient and robust to displaced tracks while having little-to-no impact on the runtime of LST. These results clearly establish that ML can be used to improve LST without penalty. Next, exploratory studies of GNN track-building algorithms are described. In particular, low-level track objects from LST are considered as nodes in a graph, where edges represent higher-level objects or even entire track candidates. Then, an edge-classifier GNN is trained, and the efficiency of the resultant edge scores is compared with that of the existing LST track quality selections. These GNN studies provide insights into the practicality and performance of using more ambitious and complex ML algorithms for HL-LHC tracking at the CMS Experiment
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Measurements of the Higgs Boson through Vector Boson Scattering and Software and Computing for Exascale Data Science
No full textThis dissertation presents the analyses of WH and VVH production through vector boson scattering (VBS). The VBS WH analysis excludes scenarios where the HWW and HZZ couplings have opposite signs beyond 5 standard deviations. The VBS VVH analysis places limits on the HHVV coupling between -0.03 and 2.04 times the Standard Model value. Both analyses are based on proton-proton collision data recorded by the CMS experiment at the CERN LHC from 2016 to 2018 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 inverse fb. In addition, two projects for the high luminosity LHC upgrade are described: a highly parallelizable track-finding algorithm and managed networking for exabyte-scale data science
Ang Pagkatuto ng Wika at Kulturang Filipino ng Diasporang Filipino sa Jeddah, Saudi Arabia
No full textThis article evaluates the methods used in teaching language, culture, and translation in Filipino at the International Philippine School in Jeddah (IPSJ), as a Philippine community school that follows the curriculum provided by the Department of Education (DepEd). This will examine the challenges faced by the teachers in IPSJ and students of the school with a multicultural set-up. This will further articulate some concepts and cultural characteristics of Saudi Arabia and the Philippines that effect a faster or slower learning capacity among students of the related languages; these may be cultural characteristics that are similar or distinct between the two nations. Finally, this article will offer a few recommendations and materials for teaching based on the advice and suggestions of six (6) teachers from IPSJ interviewed by the author about teaching Filipino language and culture
Exploring the Expressed and Perceived Discoursal Self of Multilingual Senior High School Students in Academic Writing
No full textAcademic writing, like all mediums of expression, is an act of identity, and it involves not only expert information, but also a representation of the author. Writers must carefully choose their words in order to entice, influence, and persuade their audiences (Hyland, 2002). The use of these resources, as well as the decisions made from the options they provide, reveal who the writer is. In this particular study, the researcher adds to the literature of analyzing the development of writer identity, specifically expressing the discoursal self of multilingual students. This reveals a self- representation that a writer inscribed in the text for the reader, deliberately or inadvertently (Burgess & Ivanič, 2010). This qualitative study aims to determine the extent to which the reported discoursal self is reflected in the academic writing of selected Grade 11 students in a private school in Pasig City. The researcher asked for their consent to give a copy of their article critique and college application essay in Reading and Writing Skills class, in which these were examined using metadiscoursal analysis (Hyland, 2010). They also underwent a semi-structured interview in order to see their perception on their discoursal self in academic writing, in line with the concept of writer identity by Ivanič (1998) and to see if it reflects with their projected discoursal self. Results showed that most of the students still need to familiarize and utilize the metadiscourse markers effectively in order to express their projected discoursal self well in their essays and that they mostly rely on the expectations of their teachers. However, students still have the awareness in identifying their perceived discoursal self, which mostly reflects the projected discoursal self.
Keywords: Discoursal self, Writer identity, Academic writing, Senior high schoo
Grad School: Human Growth Horror - Creative Project Entry of an Action/Adventure Computer Game Designed to Experimentally Demonstrate Viable Engineering Concepts for Educational Purposes
No full textabstract: The action/adventure game Grad School: HGH is the final, extended version of a BME Prototyping class project in which the goal was to produce a zombie-themed game that teaches biomedical engineering concepts. The gameplay provides fast paced, exciting, and mildly addicting rooms that the player must battle and survive through, followed by an engineering puzzle that must be solved in order to advance to the next room. The objective of this project was to introduce the core concepts of BME to prospective students, rather than attempt to teach an entire BME curriculum. Based on user testing at various phases in the project, we concluded that the gameplay was engaging enough to keep most users' interest through the educational puzzles, and the potential for expanding this project to reach an even greater audience is vast
400Gbps benchmark of XRootD HTTP-TPC
No full textDue to the increased demand of network traffic expected during the HL-LHC era, the T2 sites in the USA will be required to have 400Gbps of available bandwidth to their storage solution. With the above in mind we are pursuing a scale test of XRootD software when used to perform Third Party Copy transfers using the HTTP protocol. Our main objective is to understand the possible limitations in the software stack to achieve the target transfer rate; to that end we have set up a testbed of multiple XRootD servers in both UCSD and Caltech which are connected through a dedicated link capable of 400 Gbps end-to-end. Building upon our experience deploying containerized XRootD servers, we use Kubernetes to easily deploy and test different configurations of our testbed. In this work, we will present our experience doing these tests and the lessons learned
CRIU - Checkpoint Restore in Userspace for computational simulations and scientific applications
No full textCreating new materials, discovering new drugs, and simulating systems are essential processes for research and innovation and require substantial computational power. While many applications can be split into many smaller independent tasks, some cannot and may take hours or weeks to run to completion. To better manage those longer-running jobs, it would be desirable to stop them at any arbitrary point in time and later continue their computation on another compute resource; this is usually referred to as checkpointing. While some applications can manage checkpointing programmatically, it would be preferable if the batch scheduling system could do that independently. This paper evaluates the feasibility of using CRIU (Checkpoint Restore in Userspace), an open-source tool for the GNU/Linux environments, emphasizing the OSG’s OSPool HTCondor setup. CRIU allows checkpointing the process state into a disk image and can deal with both open files and established network connections seamlessly. Furthermore, it can checkpoint traditional Linux processes and containerized workloads. The functionality seems adequate for many scenarios supported in the OSPool. However, some limitations prevent it from being usable in all circumstances
CRIU - Checkpoint Restore in Userspace for computational simulations and scientific applications
No full textCreating new materials, discovering new drugs, and simulating systems are essential processes for research and innovation and require substantial computational power. While many applications can be split into many smaller independent tasks, some cannot and may take hours or weeks to run to completion. To better manage those longer-running jobs, it would be desirable to stop them at any arbitrary point in time and later continue their computation on another compute resource; this is usually referred to as checkpointing. While some applications can manage checkpointing programmatically, it would be preferable if the batch scheduling system could do that independently. This paper evaluates the feasibility of using CRIU (Checkpoint Restore in Userspace), an open-source tool for the GNU/Linux environments, emphasizing the OSG’s OSPool HTCondor setup. CRIU allows checkpointing the process state into a disk image and can deal with both open files and established network connections seamlessly. Furthermore, it can checkpoint traditional Linux processes and containerized workloads. The functionality seems adequate for many scenarios supported in the OSPool. However, some limitations prevent it from being usable in all circumstances
