36,441 research outputs found
ASCR/HEP Exascale Requirements Review Report
This draft report summarizes and details the findings, results, and
recommendations derived from the ASCR/HEP Exascale Requirements Review meeting
held in June, 2015. The main conclusions are as follows. 1) Larger, more
capable computing and data facilities are needed to support HEP science goals
in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of
the demand at the 2025 timescale is at least two orders of magnitude -- and in
some cases greater -- than that available currently. 2) The growth rate of data
produced by simulations is overwhelming the current ability, of both facilities
and researchers, to store and analyze it. Additional resources and new
techniques for data analysis are urgently needed. 3) Data rates and volumes
from HEP experimental facilities are also straining the ability to store and
analyze large and complex data volumes. Appropriately configured
leadership-class facilities can play a transformational role in enabling
scientific discovery from these datasets. 4) A close integration of HPC
simulation and data analysis will aid greatly in interpreting results from HEP
experiments. Such an integration will minimize data movement and facilitate
interdependent workflows. 5) Long-range planning between HEP and ASCR will be
required to meet HEP's research needs. To best use ASCR HPC resources the
experimental HEP program needs a) an established long-term plan for access to
ASCR computational and data resources, b) an ability to map workflows onto HPC
resources, c) the ability for ASCR facilities to accommodate workflows run by
collaborations that can have thousands of individual members, d) to transition
codes to the next-generation HPC platforms that will be available at ASCR
facilities, e) to build up and train a workforce capable of developing and
using simulations and analysis to support HEP scientific research on
next-generation systems.Comment: 77 pages, 13 Figures; draft report, subject to further revisio
Programmable image associative memory using an optical disk and a photorefractive crystal
The optical disk is a computer-addressable binary storage medium with very high capacity. More than 10^10 bits of information can be recorded on a 12-cm-diameter optical disk. The natural two-dimensional format of the data recorded on an optical disk makes this medium particularly attractive for the storage of images and holograms, while parallel access provides a convenient mechanism through which such data may be retrieved. In this paper we discuss a closed-loop optical associative memory based on the optical disk. This system incorporates image correlation, using photorefractive media to compute the best association in a shift-invariant fashion. When presented with a partial or noisy version of one of the images stored on the optical disk, the optical system evolves to a stable state in which those stored images that best match the input are temporally locked in the loop
NaNet:a low-latency NIC enabling GPU-based, real-time low level trigger systems
We implemented the NaNet FPGA-based PCI2 Gen2 GbE/APElink NIC, featuring
GPUDirect RDMA capabilities and UDP protocol management offloading. NaNet is
able to receive a UDP input data stream from its GbE interface and redirect it,
without any intermediate buffering or CPU intervention, to the memory of a
Fermi/Kepler GPU hosted on the same PCIe bus, provided that the two devices
share the same upstream root complex. Synthetic benchmarks for latency and
bandwidth are presented. We describe how NaNet can be employed in the prototype
of the GPU-based RICH low-level trigger processor of the NA62 CERN experiment,
to implement the data link between the TEL62 readout boards and the low level
trigger processor. Results for the throughput and latency of the integrated
system are presented and discussed.Comment: Proceedings for the 20th International Conference on Computing in
High Energy and Nuclear Physics (CHEP
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