121,921 research outputs found
On the robustness of Herlihy's hierarchy
A wait-free hierarchy maps object types to levels in Z(+) U (infinity) and has the following property: if a type T is at level N, and T' is an arbitrary type, then there is a wait-free implementation of an object of type T', for N processes, using only registers and objects of type T. The infinite hierarchy defined by Herlihy is an example of a wait-free hierarchy. A wait-free hierarchy is robust if it has the following property: if T is at level N, and S is a finite set of types belonging to levels N - 1 or lower, then there is no wait-free implementation of an object of type T, for N processes, using any number and any combination of objects belonging to the types in S. Robustness implies that there are no clever ways of combining weak shared objects to obtain stronger ones. Contrary to what many researchers believe, we prove that Herlihy's hierarchy is not robust. We then define some natural variants of Herlihy's hierarchy, which are also infinite wait-free hierarchies. With the exception of one, which is still open, these are not robust either. We conclude with the open question of whether non-trivial robust wait-free hierarchies exist
A Complexity-Based Hierarchy for Multiprocessor Synchronization
For many years, Herlihy's elegant computability based Consensus Hierarchy has
been our best explanation of the relative power of various types of
multiprocessor synchronization objects when used in deterministic algorithms.
However, key to this hierarchy is treating synchronization instructions as
distinct objects, an approach that is far from the real-world, where
multiprocessor programs apply synchronization instructions to collections of
arbitrary memory locations. We were surprised to realize that, when considering
instructions applied to memory locations, the computability based hierarchy
collapses. This leaves open the question of how to better capture the power of
various synchronization instructions.
In this paper, we provide an approach to answering this question. We present
a hierarchy of synchronization instructions, classified by their space
complexity in solving obstruction-free consensus. Our hierarchy provides a
classification of combinations of known instructions that seems to fit with our
intuition of how useful some are in practice, while questioning the
effectiveness of others. We prove an essentially tight characterization of the
power of buffered read and write instructions.Interestingly, we show a similar
result for multi-location atomic assignments
Low-level Vision by Consensus in a Spatial Hierarchy of Regions
We introduce a multi-scale framework for low-level vision, where the goal is
estimating physical scene values from image data---such as depth from stereo
image pairs. The framework uses a dense, overlapping set of image regions at
multiple scales and a "local model," such as a slanted-plane model for stereo
disparity, that is expected to be valid piecewise across the visual field.
Estimation is cast as optimization over a dichotomous mixture of variables,
simultaneously determining which regions are inliers with respect to the local
model (binary variables) and the correct co-ordinates in the local model space
for each inlying region (continuous variables). When the regions are organized
into a multi-scale hierarchy, optimization can occur in an efficient and
parallel architecture, where distributed computational units iteratively
perform calculations and share information through sparse connections between
parents and children. The framework performs well on a standard benchmark for
binocular stereo, and it produces a distributional scene representation that is
appropriate for combining with higher-level reasoning and other low-level cues.Comment: Accepted to CVPR 2015. Project page:
http://www.ttic.edu/chakrabarti/consensus
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