The CMS Drift Tube Trigger Track Finder

Muons are among the decay products of many new particles that may be discovered at the CERN Large Hadron Collider. At the first trigger level the identification of muons and the determination of their transverse momenta and location is performed by the Drift Tube Trigger Track Finder in the central region of the Compact Muon Solenoid experiment, using track segments detected in the Drift Tube muon chambers. Track finding is performed both in pseudorapidity and azimuth. Track candidates are ranked and sorted, and the best four are delivered to the subsequent high level trigger stage. The concept, design, control and simulation software as well as the expected performance of the system are described. Prototyping, production and tests are also summarized

Dynamic configuration of the CMS Data Acquisition cluster

The CMS Data Acquisition cluster, which runs around 10000 applications, is configured dynamically at run time. XML configuration documents determine what applications are executed on each node and over what networks these applications communicate. Through this mechanism the DAQ System may be adapted to the required performance, partitioned in order to perform (test-) runs in parallel, or re-structured in case of hardware faults. This paper presents the CMS DAQ Configurator tool, which is used to generate comprehensive configurations of the CMS DAQ system based on a high-level description given by the user. Using a database of configuration templates and a database containing a detailed model of hardware modules, data and control links, nodes and the network topology, the tool automatically determines which applications are needed, on which nodes they should run, and over which networks the event traffic will flow. The tool computes application parameters and generates the XML configuration documents as well as the configuration of the run-control system. The performance of the tool and operational experience during CMS commissioning and the first LHC runs are discussed

The Run Control and Monitoring System of the CMS Experiment

The CMS experiment at the LHC at CERN will start taking data in 2008. To configure, control and monitor the experiment during data-taking the Run Control and Monitoring System (RCMS) was developed. This paper describes the architecture and the technology used to implement the RCMS, as well as the deployment and commissioning strategy of this important component of the online software for the CMS experiment

High Level Trigger Configuration and Handling of Trigger Tables in the CMS Filter Farm

The CMS experiment at the CERN Large Hadron Collider is currently being commissioned and is scheduled to collect the first pp collision data in 2008. CMS features a two-level trigger system. The Level-1 trigger, based on custom hardware, is designed to reduce the collision rate of 40 MHz to approximately 100 kHz. Data for events accepted by the Level-1 trigger are read out and assembled by an Event Builder. The High Level Trigger (HLT) employs a set of sophisticated software algorithms, to analyze the complete event information, and further reduce the accepted event rate for permanent storage and analysis. This paper describes the design and implementation of the HLT Configuration Management system. First experiences with commissioning of the HLT system are also reported

An analysis of the control hierarchy modeling of the CMS detector control system

The supervisory level of the Detector Control System (DCS) of the CMS experiment is implemented using Finite State Machines (FSM), which model the behaviours and control the operations of all the sub-detectors and support services. The FSM tree of the whole CMS experiment consists of more than 30.000 nodes. An analysis of a system of such size is a complex task but is a crucial step towards the improvement of the overall performance of the FSM system. This paper presents the analysis of the CMS FSM system using the micro Common Representation Language 2 (mcrl2) methodology. Individual mCRL2 models are obtained for the FSM systems of the CMS sub-detectors using the ASF+SDF automated translation tool. Different mCRL2 operations are applied to the mCRL2 models. A mCRL2 simulation tool is used to closer examine the system. Visualization of a system based on the exploration of its state space is enabled with a mCRL2 tool. Requirements such as command and state propagation are expressed using modal mu-calculus and checked using a model checking algorithm. For checking local requirements such as endless loop freedom, the Bounded Model Checking technique is applied. This paper discusses these analysis techniques and presents the results of their application on the CMS FSM system

MiniDAQ-3: Providing concurrent independent subdetector data-taking on CMS production DAQ resources

The data acquisition (DAQ) of the Compact Muon Solenoid (CMS) experiment at CERN, collects data for events accepted by the Level-1 Trigger from the different detector systems and assembles them in an event builder prior to making them available for further selection in the High Level Trigger, and finally storing the selected events for offline analysis. In addition to the central DAQ providing global acquisition functionality, several separate, so-called “MiniDAQ” setups allow operating independent data acquisition runs using an arbitrary subset of the CMS subdetectors. During Run 2 of the LHC, MiniDAQ setups were running their event builder and High Level Trigger applications on dedicated resources, separate from those used for the central DAQ. This cleanly separated MiniDAQ setups from the central DAQ system, but also meant limited throughput and a fixed number of possible MiniDAQ setups. In Run 3, MiniDAQ-3 setups share production resources with the new central DAQ system, allowing each setup to operate at the maximum Level-1 rate thanks to the reuse of the resources and network bandwidth. Configuration management tools had to be significantly extended to support the synchronization of the DAQ configurations needed for the various setups. We report on the new configuration management features and on the first year of operational experience with the new MiniDAQ-3 system

The CMS Orbit Builder for the HL-LHC at CERN

The Compact Muon Solenoid (CMS) experiment at CERN incorporates one of the highest throughput data acquisition systems in the world and is expected to increase its throughput by more than a factor of ten for High-Luminosity phase of Large Hadron Collider (HL-LHC). To achieve this goal, the system will be upgraded in most of its components. Among them, the event builder software, in charge of assembling all the data read out from the different sub-detectors, is planned to be modified from a single event builder to an orbit builder that assembles multiple events at the same time. The throughput of the event builder will be increased from the current 1.6 Tb/s to 51 Tb/s for the HL-LHC orbit builder. This paper presents preliminary network transfer studies in preparation for the upgrade. The key conceptual characteristics are discussed, concerning differences between the CMS event builder in Run 3 and the CMS Orbit Builder for the HL-LHC. For the feasibility studies, a pipestream benchmark, mimicking event-builder-like traffic has been developed. Preliminary performance tests and results are discussed

Towards a container-based architecture for CMS data acquisition

The CMS data acquisition (DAQ) is implemented as a service-oriented architecture where DAQ applications, as well as general applications such as monitoring and error reporting, are run as self-contained services. The task of deployment and operation of services is achieved by using several heterogeneous facilities, custom configuration data and scripts in several languages. In this work, we restructure the existing system into a homogeneous, scalable cloud architecture adopting a uniform paradigm, where all applications are orchestrated in a uniform environment with standardized facilities. In this new paradigm DAQ applications are organized as groups of containers and the required software is packaged into container images. Automation of all aspects of coordinating and managing containers is provided by the Kubernetes environment, where a set of physical and virtual machines is unified in a single pool of compute resources. We demonstrate that a container-based cloud architecture provides an acrossthe-board solution that can be applied for DAQ in CMS. We show strengths and advantages of running DAQ applications in a container infrastructure as compared to a traditional application model

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis