Phism Polyhedral High Level Synthesis in MLIR

Polyhedral optimisation, a methodology that views nested loops as polyhedra, sounds promising for mitigating difficulties in optimising hardware designs described by high-level synthesis . But existing tools cannot meet the requirements from HLS developers for customisation and software/hardware co-optimisation . Thispaper proposes a polyhedral HLS framework built on MLIR,to address these challenges through progressive lowering multi-levelintermediate representations (IRs)…

On the Hierarchical Community Structure of Practical SAT Formulas

Modern CDCL SAT solvers easily solve industrial instances containing tens ofmillions of variables and clauses . This gap between practice and theory is a central problem insolver research . We propose parameters basedon a graph partitioning called Hierarchical Community Structure (HCS) We show that counterexamples whichplagued community structure do not apply to HCS .…

Graph Convolutional Networks for Model Based Learning in Nonlinear Inverse Problems

The majority of model-based learned image reconstruction methods in medical imaging have been limited to uniform domains such as pixelated images . If the underlying model is solved on nonuniform meshes, interpolation and embeddings are needed . This gives rise to the proposed iterative Graph ConvolutionalNewton’s Method (GCNM) The GCNM has strong generalizability to different domain shapes, out of distribution data as well as experimental data, from purely simulated training data .…

Dynamic Information Sharing and Punishment Strategies

In this paper we study the problem of information sharing among rationalself-interested agents as a dynamic game of asymmetric information . We assume agents imperfectly observe a Markov chain and they are called to decide whether they will share their noisy observations or not at each timeinstant .…

Subtyping on Nested Polymorphic Session Types

The importance of subtyping to enable a wider range of well-typed programs isundeniable . In this work, we exploreubtyping in a system of nested, recursion, and polymorphic types with acoinductive interpretation . We prove that subtyped is undecidable even for the fragment with only internal choices and nested unary recursive type constructors .…

Coordinated Motion Planning Through Randomized k Opt

This paper examines the approach taken by team gitastrophe in the CG:SHOP2021 challenge . The challenge was to find a sequence of simultaneous moves ofsquare robots between two given configurations that minimized either totaldistance travelled or makespan (total time) Our winning approach has two main components: an initialization phase that finds a good initial solution, and a$k$-opt local search phase which optimizes this solution .…

An Affective Approach for Behavioral Performance Estimation and Induction

Emotions have a major interactive role in defining how humans interact with their environment by encoding their perception to external events and influencing their cognition and decision-making process . The proposed approach monitors the behavioral performance based on the levels of Pleasure, Arousal, and Dominance (PAD) states for the human operator and when required, applies an external stimulus which is selected to induce an improvement in performance .…

Playing Against the Board Rolling Horizon Evolutionary Algorithms Against Pandemic

Competitive board games have provided a rich and diverse testbed for artificial intelligence . This paper contends that collaborative board games pose a different challenge to artificial intelligence as it must balances short-term risk mitigation with long-term winning strategies . The complex way in which the Pandemic game statechanges in a stochastic but predictable way required a number of speciallydesigned forward models, macro-action representations for decision-making, and repairing functions for the genetic operations of the evolutionary algorithm .…

Automatic differentiation for Riemannian optimization on low rank matrix and tensor train manifolds

In scientific computing and machine learning applications, matrices and moregeneral multidimensional arrays (tensors) can often be approximated with the help of low-rank decompositions . In this paper, we buildupon automatic differentiation and propose a method that, given animation of the function to be minimized, efficiently computes Riemanniangradients and matrix-by-vectors .…

Mathematics of Digital Hyperspace

Digital hyperspace is an amorphousflow of data supported by continuous streams that stretch standard concepts of type and dimension . The unstructured data of digital hyperspace can be represented, traversed, and transformed via the mathematics ofhypergraphs, hypersparse matrices, and associative array algebra .…

Euler Meets GPU Practical Graph Algorithms with Theoretical Guarantees

The Euler tour technique is a classical tool for designing parallel graphalgorithms, originally proposed for the PRAM model . We ask whether it can be adapteded to run efficiently on the GPU . We show that the Euler-based algorithms not only fulfill their theoretical promises and outperform practicalheuristics on hard instances, but also perform on par with them on easyinstances.…

Page Table Management for Heterogeneous Memory Systems

Modern enterprise servers are increasingly embracing tiered memory system . Page table pages can end up on NVMM even when enough DRAM memory is available . This improves the runtimeby 20% on an average for a set of synthetic and real-world large memoryfootprint applications when compared with various default Linux kerneltechniques .…

Detection of Functional Communities in Networks of Randomly Coupled Oscillators Using the Dynamic Mode Decomposition

Dynamic-mode decomposition (DMD) is a versatile framework for model-freeanalysis of time series that are generated by dynamical systems . We develop aDMD-based algorithm to investigate the formation of “functional communities” in networks of coupled, heterogeneous Kuramoto oscillators . In these functionalcommunities, the oscillators in the network have similar dynamics .…

IEEE 802 11bf Toward Ubiquitous Wi Fi Sensing

IEEE 802.11bf Task Group is defining the appropriatemodifications to existing Wi-Fi standards to enhance sensing capabilities . We discuss some of the most interesting proposed technical features so far . We also introduce a roadmap of research challenges pertaining to Wi-fi sensing and its integration with future technologies and emerging spectrum bands .…

SkyQuery An Aerial Drone Video Sensing Platform

Video-based sensing from aerial drones can provide rich data for numerous applications, including traffic analysis . SkyQuery is a novel aerial drone video sensing platform that provides an expressive, high-level programming language . We conduct diverse case studies usingSkyQuery in parking monitoring, pedestrian activity mapping, and traffic hazard detection scenarios to demonstrate the generalizability and effectiveness of our system .…

Scheduling of Wireless Edge Networks for Feedback Based Interactive Applications

Interactive applications with automated feedback will largely influence thedesign of future networked infrastructures . The quality-of-service parameter for such applications is the end-to-end latency over the entire loop . By modelling the communicationof a feedback loop as a two-hop network, we address the problem of allocating resources in order to minimize the delay violation probability (DVP),i.e.…

Page Table Management for Heterogeneous Memory Systems

Modern enterprise servers are increasingly embracing tiered memory system . Page table pages can end up on NVMM even when enough DRAM memory is available . This improves the runtimeby 20% on an average for a set of synthetic and real-world large memoryfootprint applications when compared with various default Linux kerneltechniques .…

A comparison of two approaches for measuring interdisciplinary research output the disciplinary diversity of authors vs the disciplinary diversity of the reference list

This study investigates the convergence of two bibliometric approaches to themeasurement of interdisciplinary research . In general, diversity of the reference list grows with the number of fields reflected in a paper’s authors’ list . However, this tendency varies across disciplines, and noticeable exceptions are found at individual paper level .…

Few shot Semantic Image Synthesis Using StyleGAN Prior

This paper tackles a challenging problem of generating photorealistic images from semantic layouts in few-shot scenarios . We present atraining strategy that performs pseudo labeling of semantic masks using theStyleGAN prior . Our framework cansynthesize high-quality images from not only dense semantic masks but alsosparse inputs such as landmarks and scribbles .…

A Simple Logic of Functional Dependence

This paper presents a simple decidable logic of functional dependence LFD . It is based on an extension of classical propositional logic with dependence atoms plus dependence quantifiers treated as modalities . The expressivestrength, complete proof calculus and meta-properties of LFD are explored .…

Experimental check of model of object innovation evaluation

The article discusses the approach for evaluating the innovation index of the products and technologies . The evaluation results can be used to create an awarehouse of the object descriptions with significant innovation potential . The cyclical nature of dynamicchanges in indicators, their interdependence was established, some generalfeatures of products promotion were found.…

Committee Voting with Incomplete Approvals

We investigate approval-based committee voting with incomplete information about voters’ approval preferences . We consider several models ofincompleteness where each voter partitions the set of candidates into approved,disapproved, and unknown candidates . We study the complexity of some fundamental problems such as determining whether a given committee is apossible or necessary winning committee and whether it possibly or necessarilysatisfies representation axioms .…

Multi Robot Distributed Semantic Mapping in Unfamiliar Environments through Online Matching of Learned Representations

Most state-of-the-art semantic mapping systems are based on supervised learning algorithms that cannot classify novel observations online . We present a solution to multi-robot distributed semantic mapping of noveland unfamiliar environments . Compared to the state ofthe art, the proposed solution produces 20-60% higher quality global maps that do not degrade even as many more local maps are fused .…

Control of Agreement and Disagreement Cascades with Distributed Inputs

A cascade of opinionformation spreads through a group of networked decision-makers in response to adistributed input signal . Using a nonlinear opinion dynamics model, we show how the triggering of anopinion cascade and the collective decision itself depend on both thedistributed input and the node agreement and disagreement centrality, determined by the spectral properties of the network graph .…

Cache Efficient Fork Processing Patterns on Large Graphs

As large graph processing emerges, we observe a costly fork-processingpattern (FPP) common in many graph algorithms . The unique feature of the FPP is that it launches many independent queries from different source vertices on the same graph . We propose ForkGraph, a cache-efficient FPP processing system on multi-core architectures, to improve the cache reuse of the graph .…

On Symmetry and Quantification A New Approach to Verify Distributed Protocols

Proving that an unbounded distributed protocol satisfies a given safetyproperty amounts to finding a quantified inductive invariant that implies the property for all possible instance sizes of the protocol . We propose symmetricincremental induction, an extension of the finite-domain IC3/PDR algorithm, that automatically derives the required quantified induction ant byexploiting the connection between symmetry and quantification .…

Determination of weight coefficients for additive fitness function of genetic algorithm

The paper gives a formal description of analgorithm fitness function, which is a weighted sum of three heterogeneouscriteria . The selected methods for analytical determining of weight factors are described in detail . The authors present a research methodology using the experimental results from earlier in the discussed project “Data Warehouse Support on theBase Intellectual Web Crawler and Evolutionary Model for Target InformationSelection”.…

Say It All Feedback for Improving Non Visual Presentation Accessibility

Presentation A11y is a system that provides real-time and post-presentation accessibility feedback . 72% of 610 visual elements (e.g., images, text) were insufficiently described . Presenters using our system with their own slide-basedpresentations described more of the content on their slides, and identified 3.26 times more accessibility problems to fix after the talk than when using atraditional slide based interface .…

FeatureEnVi Visual Analytics for Feature Engineering Using Stepwise Selection and Semi Automatic Extraction Approaches

FeatureEnVi is a visual analytics system specifically designed to assist with the feature engineering process of machine learning . Feature engineering can be very beneficial for ML, leading to numerous improvements suchas boosting the predictive results, decreasing computational times, reducing noise, and increasing the transparency behind the decisions takenduring the training .…

Challenges for Optical Flow Estimates in Elastography

In this paper, we consider visualization of displacement fields via opticalflow methods in elastographic experiments consisting of a static compression of a sample . We propose an elastography optical flow method (EOFM) which takes into account experimental constraints, such as appropriate boundary conditions and the use of speckle information .…