We consider the models of distributed computation defined as subsets of the runs of the iterated immediate snapshot model. Given a task @math and a model @math , we provide topological conditions for @math to be solvable in @math . When applied to the wait-free model, our conditions result in the celebrated Asynchronous Computability Theorem (ACT) of Herlihy and Shavit. To demonstrate the utility of our characterization, we consider a task that has been shown earlier to admit only a very complex @math -resilient solution. In contrast, our generalized computability theorem confirms its @math -resilient solvability in a straightforward manner.
The IIS model was introduced by Borowsky and Gafni @cite_18 and shown to precisely capture the standard chromatic subdivision of the input complex @cite_14 @cite_5 . Due to the elegance of its topological representation, IIS has been widely used topological reasoning about distributed computing @cite_30 @cite_9 @cite_18 @cite_31 @cite_2 . @cite_18 @cite_24 , IIS has been shown equivalent to SM in terms of task solvability. @cite_6 and, more recently, Raynal and Stainer @cite_20 relate proper subsets of sub-IIS and sub-SM models restricted using specific failure detectors. A recent paper @cite_10 extends these equivalences to arbitrary sub-SM and sub-IIS models, thus justifying the choice of IIS as a model of study.
@cite_30 @cite_18 @cite_14 @cite_9 @cite_6 @cite_24 @cite_2 @cite_5 @cite_31 @cite_10 @cite_20
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The Iterated Immediate Snapshot model (IIS), due to its elegant topological representation, has become standard for applying topological reasoning to distributed computing. In this paper, we focus on relations between IIS and the more realistic (non-iterated) read-write Atomic- Snapshot memory model (AS). We grasp equivalences between subsets of runs of AS and IIS (we call them sub-IIS and sub-AS models). To establish an equivalence between a sub-AS model M and a sub-IIS model M', we need two algorithms, a forward simulation F : AS -> IIS and a backward simulation B: IIS -> AS, such that B(F(M)) is a subset of M and F(B(M')) is a subset of M'. AS and IIS are provided with such simulations and, thus, they have the same task computability power. However, the relations between proper sub-AS and sub-IIS models remained unclear until now. In this paper, we present a two-way simulation protocol that provides an equivalent sub-IIS model for any adversarial sub-AS model, i.e., for any sub-AS model specified by the sets of live processes. We achieve the result by ensuring that, under the two-way simulation, the set of live processes in an AS run coincides with the set of fast processes in the simulated IIS run, and vice versa. Random graph models with limited choice have been studied extensively with the goal of understanding the mechanism of the emergence of the giant component. One of the standard models are the Achlioptas random graph processes on a fixed set of (n ) vertices. Here at each step, one chooses two edges uniformly at random and then decides which one to add to the existing configuration according to some criterion. An important class of such rules are the bounded-size rules where for a fixed (K 1 ), all components of size greater than (K ) are treated equally. While a great deal of work has gone into analyzing the subcritical and supercritical regimes, the nature of the critical scaling window, the size and complexity (deviation from trees) of the components in the critical regime and nature of the merging dynamics has not been well understood. In this work we study such questions for general bounded-size rules. Our first main contribution is the construction of an extension of Aldous’s standard multiplicative coalescent process which describes the asymptotic evolution of the vector of sizes and surplus of all components. We show that this process, referred to as the standard augmented multiplicative coalescent (AMC) is ‘nearly’ Feller with a suitable topology on the state space. Our second main result proves the convergence of suitably scaled component size and surplus vector, for any bounded-size rule, to the standard AMC. This result is new even for the classical Erdős–Renyi setting. The key ingredients here are a precise analysis of the asymptotic behavior of various susceptibility functions near criticality and certain bounds from (The barely subcritical regime. Arxiv preprint, 2012) on the size of the largest component in the barely subcritical regime. In this paper, we present a two-level generative model for representing the images and surface depth maps of drapery and clothes. The upper level consists of a number of folds which will generate the high contrast (ridge) areas with a dictionary of shading primitives (for 2D images) and fold primitives (for 3D depth maps). These primitives are represented in parametric forms and are learned in a supervised learning phase using 3D surfaces of clothes acquired through photometric stereo. The lower level consists of the remaining flat areas which fill between the folds with a smoothness prior (Markov random field). We show that the classical ill-posed problem-shape from shading (SFS) can be much improved by this two-level model for its reduced dimensionality and incorporation of middle-level visual knowledge, i.e., the dictionary of primitives. Given an input image, we first infer the folds and compute a sketch graph using a sketch pursuit algorithm as in the primal sketch (, 2003). The 3D folds are estimated by parameter fitting using the fold dictionary and they form the "skeleton" of the drapery cloth surfaces. Then, the lower level is computed by conventional SFS method using the fold areas as boundary conditions. The two levels interact at the final stage by optimizing a joint Bayesian posterior probability on the depth map. We show a number of experiments which demonstrate more robust results in comparison with state-of-the-art work. In a broader scope, our representation can be viewed as a two-level inhomogeneous MRF model which is applicable to general shape-from-X problems. Our study is an attempt to revisit Marr's idea (Marr and Freeman, 1982) of computing the 2frac12D sketch from primal sketch. In a companion paper (Barbu and Zhu, 2005), we study shape from stereo based on a similar two-level generative sketch representation. Mulmuley [Mul12a] recently gave an explicit version of Noether’s Normalization lemma for ring of invariants of matrices under simultaneous conjugation, under the conjecture that there are deterministic black-box algorithms for polynomial identity testing (PIT). He argued that this gives evidence that constructing such algorithms for PIT is beyond current techniques. In this work, we show this is not the case. That is, we improve Mulmuley’s reduction and correspondingly weaken the conjecture regarding PIT needed to give explicit Noether Normalization. We then observe that the weaker conjecture has recently been nearly settled by the authors ([FS12]), who gave quasipolynomial size hitting sets for the class of read-once oblivious algebraic branching programs (ROABPs). This gives the desired explicit Noether Normalization unconditionally, up to quasipolynomial factors. As a consequence of our proof we give a deterministic parallel polynomial-time algorithm for deciding if two matrix tuples have intersecting orbit closures, under simultaneous conjugation. We also study the strength of conjectures that Mulmuley requires to obtain similar results as ours. We prove that his conjectures are stronger, in the sense that the computational model he needs PIT algorithms for is equivalent to the well-known algebraic branching program (ABP) model, which is provably stronger than the ROABP model. Finally, we consider the depth-3 diagonal circuit model as defined by Saxena [Sax08], as PIT algorithms for this model also have implications in Mulmuley’s work. Previous work (such as [ASS12] and [FS12]) have given quasipolynomial size hitting sets for this model. In this work, we give a much simpler construction of such hitting sets, using techniques of Shpilka and Volkovich [SV09].