10,785 research outputs found
Computational Techniques for Efficient Conversion of Image Files from Area Detectors
Area detectors are used in many scientific and technological applications
such as particle and radiation physics. Thanks to the recent technological
developments, the radiation sources are becoming increasingly brighter and the
detectors become faster and more efficient. The result is a sharp increase in
the size of data collected in a typical experiment. This situation imposes a
bottleneck on data processing capabilities, and could pose a real challenge to
scientific research in certain areas. This article proposes a number of simple
techniques to facilitate rapid and efficient extraction of data obtained from
these detectors. These techniques are successfully implemented and tested in a
computer program to deal with the extraction of X-ray diffraction patterns from
EDF image files obtained from CCD detectors.Comment: 16 pages, 6 figure
Real-time disk scheduling in a mixed-media file system
This paper presents our real-time disk scheduler called the Delta L scheduler, which optimizes unscheduled best-effort disk requests by giving priority to best-effort disk requests while meeting real-time request deadlines. Our scheduler tries to execute real-time disk requests as much as possible in the background. Only when real-time request deadlines are endangered, our scheduler gives priority to real-time disk requests. The Delta L disk scheduler is part of our mixed-media file system called Clockwise. An essential part of our work is extensive and detailed raw disk performance measurements. The Delta L disk scheduler for its real-time schedulability analysis and to decide whether scheduling a best-effort request before a real-time request violates real-time constraints uses these raw performance measurements. Further, a Clockwise off-line simulator uses the raw performance measurements where a number of different disk schedulers are compared. We compare the Delta L scheduler with a prioritizing Latest Start Time (LST) scheduler and non-prioritizing EDF scheduler. The Delta L scheduler is comparable to LST in achieving low latencies for best-effort requests under light to moderate real-time loads and better in achieving low latencies for best-effort requests for extreme real-time loads. The simulator is calibrated to an actual Clockwise. Clockwise runs on a 200MHz Pentium-Pro based PC with PCI bus, multiple SCSI controllers and disks on Linux 2.2.x and the Nemesis kernel. Clockwise performance is dictated by the hardware: all available bandwidth can be committed to real-time streams, provided hardware overloads do not occur
Linear response strength functions with iterative Arnoldi diagonalization
We report on an implementation of a new method to calculate RPA strength
functions with iterative non-hermitian Arnoldi diagonalization method, which
does not explicitly calculate and store the RPA matrix. We discuss the
treatment of spurious modes, numerical stability, and how the method scales as
the used model space is enlarged. We perform the particle-hole RPA benchmark
calculations for double magic nucleus 132Sn and compare the resulting
electromagnetic strength functions against those obtained within the standard
RPA.Comment: 9 RevTeX pages, 11 figures, submitted to Physical Review
TimeTrader: Exploiting Latency Tail to Save Datacenter Energy for On-line Data-Intensive Applications
Datacenters running on-line, data-intensive applications (OLDIs) consume
significant amounts of energy. However, reducing their energy is challenging
due to their tight response time requirements. A key aspect of OLDIs is that
each user query goes to all or many of the nodes in the cluster, so that the
overall time budget is dictated by the tail of the replies' latency
distribution; replies see latency variations both in the network and compute.
Previous work proposes to achieve load-proportional energy by slowing down the
computation at lower datacenter loads based directly on response times (i.e.,
at lower loads, the proposal exploits the average slack in the time budget
provisioned for the peak load). In contrast, we propose TimeTrader to reduce
energy by exploiting the latency slack in the sub- critical replies which
arrive before the deadline (e.g., 80% of replies are 3-4x faster than the
tail). This slack is present at all loads and subsumes the previous work's
load-related slack. While the previous work shifts the leaves' response time
distribution to consume the slack at lower loads, TimeTrader reshapes the
distribution at all loads by slowing down individual sub-critical nodes without
increasing missed deadlines. TimeTrader exploits slack in both the network and
compute budgets. Further, TimeTrader leverages Earliest Deadline First
scheduling to largely decouple critical requests from the queuing delays of
sub- critical requests which can then be slowed down without hurting critical
requests. A combination of real-system measurements and at-scale simulations
shows that without adding to missed deadlines, TimeTrader saves 15-19% and
41-49% energy at 90% and 30% loading, respectively, in a datacenter with 512
nodes, whereas previous work saves 0% and 31-37%.Comment: 13 page
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