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

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

Flexible custom designs for CMS DAQ

The CMS central DAQ system is built using commercial hardware (PCs and networking equipment), except for two components: the Front-end Readout Link (FRL) and the Fast Merger Module (FMM). The FRL interfaces the sub-detector specific front-end electronics to the central DAQ system in a uniform way. The FRL is a compact-PCI module with an additional PCI 64bit connector to host a Network Interface Card (NIC). On the sub-detector side, the data are written to the link using a FIFO-like protocol (SLINK64). The link uses the Low Voltage Differential Signal (LVDS) technology to transfer data with a throughput of up to 400 MBytes/s. The FMM modules collect status signals from the front-end electronics of the sub-detectors, merge and monitor them and provide the resulting signals with low latency to the first level trigger electronics. In particular, the throttling signals allow the trigger to avoid buffer overflows and data corruption in the front-end electronics when the data produced in the front-end exceeds the capacity of the DAQ system. Both cards are compact-PCI cards with a 6U form factor. They are implemented with FPGAs. The main FPGA implements the processing logic of the card and the interfaces to the variety of busses on the card. Another FPGA contains a custom compact-PCI interface for configuration, control and monitoring. The chosen technology provides flexibility to implement new features if required

The terabit/s super-fragment builder and trigger throttling system for the compact muon solenoid experiment at CERN

The Data Acquisition System of the Compact Muon Solenoid experiment at the Large Hadron Collider reads out event fragments of an average size of 2 kilobytes from around 650 detector front-ends at a rate of up to 100 kHz. The first stage of event-building is performed by the Super-Fragment Builder employing custom-built electronics and a Myrinet optical network. It reduces the number of fragments by one order of magnitude, thereby greatly decreasing the requirements for the subsequent event-assembly stage. By providing fast feedback from any of the front-ends to the trigger, the Trigger Throttling System prevents buffer overflows in the front-end electronics due to variations in the size and rate of events or due to back-pressure from the down-stream event-building and processing. This paper reports on new performance measurements and on the recent successful integration of a scaled-down setup of the described system with the trigger and with front-ends of all major sub-detectors. The on-going commissioning of the full-scale system is discussed

High availability through full redundancy of the CMS detector controls system

The CMS detector control system (DCS) is responsible for controlling and monitoring the detector status and for the operation of all CMS sub detectors and infrastructure. This is required to ensure safe and efficient data taking so that high quality physics data can be recorded. The current system architecture is composed of more than 100 servers in order to provide the required processing resources. An optimization of the system software and hardware architecture is under development to ensure redundancy of all the controlled sub-systems and to reduce any downtime due to hardware or software failures. The new optimized structure is based mainly on powerful and highly reliable blade servers and makes use of a fully redundant approach, guaranteeing high availability and reliability. The analysis of the requirements, the challenges, the improvements and the optimized system architecture as well as its specific hardware and software solutions are presented

Status of the CMS Detector Control System

The Compact Muon Solenoid (CMS) is a CERN multi-purpose experiment that exploits the physics of the Large Hadron Collider (LHC). The Detector Control System (DCS) ensures a safe, correct and efficient experiment operation, contributing to the recording of high quality physics data. The DCS is programmed to automatically react to the LHC operational mode. CMS sub-detectors' bias voltages are set depending on the machine mode and particle beam conditions. An operator provided with a small set of screens supervises the system status summarized from the approximately 6M monitored parameters. Using the experience of nearly two years of operation with beam the DCS automation software has been enhanced to increase the system efficiency by minimizing the time required by sub detectors to prepare for physics data taking. From the infrastructure point of view the DCS will be subject to extensive modifications in 2012. The current rack mounted control PCs will be exchanged by a redundant pair of DELL Blade systems. These blades are a high-density modular solution that incorporates servers and networking into a single chassis that provides shared power, cooling and management. This infrastructure modification will challenge the DCS software and hardware factorization capabilities. The on going studies for this migration together with the latest modifications are discussed in the paper

Infrastructures and Monitoring of the on-line CMS computing centre

This paper describes in detail the infrastructure and installation of the CMS on-line computing centre (CMSOLC) and its associated monitoring system. In summer 2007, 640 PCs acting as detector Readout Units for the CMS Data Acquisition System (DAQ) were deployed along with ~150 servers for DAQ general services. Since summer 2008, ~900 PCs acting as DAQ Event Builder Units/Filter Units have been added and today, the CMSOLC has an on-line processing capability sufficient for a Level 1 trigger accept rate of 50 kHz. To ensure that these ~1700 PCs are running efficiently, a multi-level monitoring system has been put in place. This system is also described in this paper