No abstract available

[en] The most ambitious implementation of the Jefferson Lab data acquisition system (CODA) to date is for the CLAS spectrometer in Experimental Hall B. CLAS has over 40,000 instrumented channels and uses up to 30 front-end (FASTBUS/VME) crates in the DAQ subsystem. During the initial experiments the authors found that performance of the fully instrumented DAQ system did not scale as expected based on single point to point benchmarks. Over the past year the authors have been able to study various performance bottlenecks in the CLAS DAQ system including front-end real time performance, switched 100BaseT Ethernet data transport, and online data distribution and recording. Performance tuning was necessary for components on both real time (VxWorks) and UNIX (Solaris) operating systems. In addition, a new efficient Event Transfer System (ET) was developed to provide faster online monitoring while having minimal impact on data throughput to storage. They discuss these issues and efforts to overcome the real world problems associated with running a high performance DAQ system on a variety of commercial hardware and software

[en] The Event Transfer system enables its users to produce events (data) and share them with other users by utilizing shared memory on either Solaris or Linux-based computers. Its design emphasizes speed, reliability, ease of use, and recoverability from crashes. In addition to fast local operation, the ET system allows network transfer of events. Using multi-threaded code based on POSIX threades and mutexes, a successful implementation was developed which allowed passing events over 500 kHz on a 4 cpu Sun workstation and 150 kHz on a dual cpu PC

[en] The authors discuss the design and performance of a Trigger Supervisor System for use in nuclear physics experiments at Jefferson Lab. They also discuss the enhanced features of a new Trigger Supervisor Module now under construction

[en] Optimal sensitivity in large HPGe γ-ray spectrometers such as Gammasphere and Euroball is achieved with 4-fold γ-ray coincidences or higher. Analysis of coincidence data at these folds is difficult as storage constraints make histogram-based techniques impractical. To address the problem of efficient storage of and access to high-fold coincidence data we have developed Blue, a specialized database program. Each coincidence event in this database is stored in its native fold eliminating statistical artifacts which can be introduced by unfolding a high-fold event to several lower-fold events. Partition of the dataset is based on the density distribution of coincidence events which makes data access efficient. A simple yet flexible query system is implemented by using a tree-like index for these partitions. This program is capable of executing a variety of queries, such as taking gates on a multi-fold database, at timescales which are interactive (s) or near-interactive (min). Simple compression techniques are employed so that databases with sizes of 10⁹ coincidences can easily be stored in a space of 10 Gb or less

No abstract available

No abstract available

[en] We discuss a γ-ray tracking algorithm that has been developed for the proposed gamma-ray energy tracking array (GRETA). This algorithm has been designed so as to maximize the resolving power for detecting high-multiplicity γ-ray events. The conceptual basis for this algorithm will be presented. In addition, Monte Carlo simulated data will be used to assess performance over a large range of relevant parameters. A discussion of the potential γ-ray polarimeter performance of GRETA is also presented

No abstract available

No abstract available