19,529 research outputs found
Optimizing I/O for Big Array Analytics
Big array analytics is becoming indispensable in answering important
scientific and business questions. Most analysis tasks consist of multiple
steps, each making one or multiple passes over the arrays to be analyzed and
generating intermediate results. In the big data setting, I/O optimization is a
key to efficient analytics. In this paper, we develop a framework and
techniques for capturing a broad range of analysis tasks expressible in
nested-loop forms, representing them in a declarative way, and optimizing their
I/O by identifying sharing opportunities. Experiment results show that our
optimizer is capable of finding execution plans that exploit nontrivial I/O
sharing opportunities with significant savings.Comment: VLDB201
Omphale: Streamlining the Communication for Jobs in a Multi Processor System on Chip
Our Multi Processor System on Chip (MPSoC) template provides processing tiles that are connected via a network on chip. A processing tile contains a processing unit and a Scratch Pad Memory (SPM). This paper presents the Omphale tool that performs the first step in mapping a job, represented by a task graph, to such an MPSoC, given the SPM sizes as constraints. Furthermore a memory tile is introduced. The result of Omphale is a Cyclo Static DataFlow (CSDF) model and a task graph where tasks communicate via sliding windows that are located in circular buffers. The CSDF model is used to determine the size of the buffers and the communication pattern of the data. A buffer must fit in the SPM of the processing unit that is reading from it, such that low latency access is realized with a minimized number of stall cycles. If a task and its buffer exceed the size of the SPM, the task is examined for additional parallelism or the circular buffer is partly located in a memory tile. This results in an extended task graph that satisfies the SPM size constraints
Properties of pedestrians walking in line: Stepping behavior
In human crowds, interactions among individuals give rise to a variety of
self-organized collective motions that help the group to effectively solve the
problem of coordination. However, it is still not known exactly how humans
adjust their behavior locally, nor what are the direct consequences on the
emergent organization. One of the underlying mechanisms of adjusting individual
motions is the stepping dynamics. In this paper, we present first quantitative
analysis on the stepping behavior in a one-dimensional pedestrian flow studied
under controlled laboratory conditions. We find that the step length is
proportional to the velocity of the pedestrian, and is directly related to the
space available in front of him, while the variations of the step duration are
much smaller. This is in contrast with locomotion studies performed on isolated
pedestrians and shows that the local density has a direct influence on the
stepping characteristics. Furthermore, we study the phenomena of
synchronization -walking in lockstep- and show its dependence on flow
densities. We show that the synchronization of steps is particularly important
at high densities, which has direct impact on the studies of optimizing
pedestrians flow in congested situations. However, small synchronization and
antisynchronization effects are found also at very low densities, for which no
steric constraints exist between successive pedestrians, showing the natural
tendency to synchronize according to perceived visual signals.Comment: 8 pages, 5 figure
Optimal Precoders for Tracking the AoD and AoA of a mm-Wave Path
In millimeter-wave channels, most of the received energy is carried by a few
paths. Traditional precoders sweep the angle-of-departure (AoD) and
angle-of-arrival (AoA) space with directional precoders to identify directions
with largest power. Such precoders are heuristic and lead to sub-optimal
AoD/AoA estimation. We derive optimal precoders, minimizing the Cram\'{e}r-Rao
bound (CRB) of the AoD/AoA, assuming a fully digital architecture at the
transmitter and spatial filtering of a single path. The precoders are found by
solving a suitable convex optimization problem. We demonstrate that the
accuracy can be improved by at least a factor of two over traditional
precoders, and show that there is an optimal number of distinct precoders
beyond which the CRB does not improve.Comment: Resubmission to IEEE Trans. on Signal Processing. 12 pages and 9
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