CHARM-Card: Hardware Based Cluster Control And Management System

Die Selektion und Analyse von Ereignisdaten des Schwerionen-Experiments ALICE am CERN werden durch sogenannte Triggerstufen vorgenommen. Der High Level Trigger (HLT) ist die letzte Triggerstufe des Experimentes. Er besteht aus einer Rechnerfarm von zur Zeit über 120 Computer, die auf 300 Rechner ausgebaut werden soll. Die manuelle Installation, Konfiguration und Wartung einer Rechnerfarm dieser Größe sind dabei jedoch sehr aufwändig und zeitintensiv. Die vorliegende Arbeit beschreibt die Implementierung und Funktionsweise einer autonomen Steuereinheit, die in jedem Rechner des HLT Computer Clusters eingebaut wurde. Die Hauptaufgaben der Steuereinheit sind die Fernsteuerung der Knoten und die automatische Installation, Überwachung und Wartung derselben. Ein weiteres erreichtes Ziel ist die universelle Nutzung der Steuereinheit: Denn aufgrund der heterogenen Clusterstruktur durfte es keine Einschränkungen für den Betrieb der Steuereinheit bezüglich des Rechnermodells oder des Betriebssystems der Clusterknoten geben. Dadurch lassen sich auch kostengünstige COTS (commercial-off-the-shelf) Rechner als Knoten einsetzen, ohne dabei auf die Fernwartungsfunktionen zu verzichten, wie sie in teuren Serverrechner zu finden sind. Die Steuereinheit ist bereits im Einsatz und ermöglicht die Fernwartung aller Rechner des HLT Clusters. Des Weiteren wurde die gesamte HLT Rechnerfarm mit Hilfe der Steuereinheit automatisch installiert, getestet und konfiguriert

First experiences with the implementation of the European standard EN 62304 on medical device software for the quality assurance of a radiotherapy unit

BACKGROUND: According to the latest amendment of the Medical Device Directive standalone software qualifies as a medical device when intended by the manufacturer to be used for medical purposes. In this context, the EN 62304 standard is applicable which defines the life-cycle requirements for the development and maintenance of medical device software. A pilot project was launched to acquire skills in implementing this standard in a hospital-based environment (in-house manufacture). METHODS: The EN 62304 standard outlines minimum requirements for each stage of the software life-cycle, defines the activities and tasks to be performed and scales documentation and testing according to its criticality. The required processes were established for the pre-existent decision-support software FlashDumpComparator (FDC) used during the quality assurance of treatment-relevant beam parameters. As the EN 62304 standard implicates compliance with the EN ISO 14971 standard on the application of risk management to medical devices, a risk analysis was carried out to identify potential hazards and reduce the associated risks to acceptable levels. RESULTS: The EN 62304 standard is difficult to implement without proper tools, thus open-source software was selected and integrated into a dedicated development platform. The control measures yielded by the risk analysis were independently implemented and verified, and a script-based test automation was retrofitted to reduce the associated test effort. After all documents facilitating the traceability of the specified requirements to the corresponding tests and of the control measures to the proof of execution were generated, the FDC was released as an accessory to the HIT facility. CONCLUSIONS: The implementation of the EN 62304 standard was time-consuming, and a learning curve had to be overcome during the first iterations of the associated processes, but many process descriptions and all software tools can be re-utilized in follow-up projects. It has been demonstrated that a standards-compliant development of small and medium-sized medical software can be carried out by a small team with limited resources in a clinical setting. This is of particular relevance as the upcoming revision of the Medical Device Directive is expected to harmonize and tighten the current legal requirements for all European in-house manufacturers

CHARM-Card: Hardwarebasiertes Clusterkontroll- und Clustermanagementsystem

The selection and analysis of detector events of the heavy ion collider experiment ALICE at CERN are accomplished by the so-called trigger levels. The High Level Trigger (HLT) is the last trigger level of this experiment. Currently, it consists of up to over 120 computers and it is planned to upgrade the cluster to up to 300 computers. However, the manual installation, configuration and maintenance of such a big computer farm require a large amount of administrative effort. This thesis describes the implementation and functionality of an autonomous control unit, which was installed to every node of the HLT computing cluster. The main tasks of the control unit are the remote control of the cluster nodes and the automatic installation, monitoring and maintenance of the computers. By the reason of the heterogeneous layout of the target cluster, the control unit was developed to be flexible in use independent of the computer model or operating system of the cluster node. This characteristic enables remote control of cost-efficient COTS (commercial-off-the-shelf) PCs, which do not have integrated remote control capabilities as expensive server boards. The HLT computing cluster is already remotely controlled by the help of the control unit. Furthermore, this control unit was also used for the automatic setup, testing and configuration of all cluster nodes

Progressive multifocal leukoencephalopathy and immune reconstitution inflammatory syndrome in seven patients with sarcoidosis: a critical discussion of treatment and prognosis

Progressive multifocal leukoencephalopathy (PML) is a subacute brain infection by the opportunistic John Cunningham (JC) virus. Herein, we describe seven patients with PML, lymphopenia, and sarcoidosis, in three of whom PML was the first manifestation of sarcoidosis. At onset, the clinical picture comprised rapidly progressive spastic hemi- or limb pareses as well as disturbances of vision, speech, and orientation. Cerebral magnetic resonance imaging showed T2-hyperintense, confluent, mainly supratentorial lesions. Four patients developed punctate contrast enhancement as a radiological sign of an immune reconstitution inflammatory syndrome (IRIS), three of them having a fatal course. In the cerebrospinal fluid, the initial JC virus load (8–25,787 copies/ml) did not correlate with interindividual severity; however, virus load corresponded to clinical dynamics. Brain biopsies ( n  = 2), performed 2 months after symptom onset, showed spotted demyelination and microglial activation. All patients had lymphopenia in the range of 270–1150/µl. To control JC virus, three patients received a combination of mirtazapine and mefloquine, another two patients additionally took cidofovir. One patient was treated with cidofovir only, and one patient had a combined regimen with mirtazapine, mefloquine, cidofovir, intravenous interleukin 2, and JC capsid vaccination. To treat sarcoidosis, the four previously untreated patients received prednisolone. Three patients had taken immunosuppressants prior to PML onset, which were subsequently stopped as a potential accelerator of opportunistic infections. After 6–54 months of follow up, three patients reached an incomplete recovery, one patient progressed, but survived so far, and two patients died. One further patient was additionally diagnosed with lung cancer, which he died from after 24 months. We conclude that the combination of PML and sarcoidosis is a diagnostic and therapeutic challenge. PML can occur as the first sign of sarcoidosis without preceding immunosuppressive treatment. The development of IRIS might be an indicator of poor outcome

ALICE HLT High Speed Tracking on GPU

The on-line event reconstruction in ALICE is performed by the High Level Trigger, which should process up to 2000 events per second in proton-proton collisions and up to 300 central events per second in heavy-ion collisions, corresponding to an inp ut data stream of 30 GB/s. In order to fulfill the time requirements, a fast on-line tracker has been developed. The algorithm combines a Cellular Automaton method being used for a fast pattern recognition and the Kalman Filter method for fitting of found trajectories and for the final track selection. The tracker was adapted to run on Graphics Processing Units (GPU) using the NVIDIA Compute Unified Device Architecture (CUDA) framework. The implementation of the algorithm had to be adjusted at many points to allow for an efficient usage of the graphics cards. In particular, achieving a good overall workload for many processor cores, efficient transfer to and from the GPU, as well as optimized utilization of the different memories the GPU offers turned out to be critical. To cope with these problems a dynamic scheduler was introduced, which redistributes the workload among the processor cores. Additionally a pipeline was implemented so that the tracking on the GPU, the initialization and the output process ed by the CPU, as well as the DMA transfer can overlap. The GPU tracking algorithm significantly outperforms the CPU version for large events while it entirely maintains its efficiency