Tootfinder

New article out with @…!
"Live Notation for Patterns of Movement"
If computer programming languages can be used to control the movement of robots, they can therefore be used as choreographic notations. Weaving, dance, and musical forms can be taken as places of inspiration for this, bringing together patterns, computation, movement, and notation in live telem…

Started re-reading David Golumbia's "The Cultural Logic of Computation".
And hell does that make me miss David and his voice these days. This book is so far ahead of its time, so clear ... if I ever write something half as good, I'll have punched way above my weight.

A Joint Communication and Computation Design for Distributed RISs Assisted Probabilistic Semantic Communication in IIoT
Zhouxiang Zhao, Zhaohui Yang, Chongwen Huang, Li Wei, Qianqian Yang, Caijun Zhong, Wei Xu, Zhaoyang Zhang
https://arxiv.org/abs/2404.19750

A Joint Communication and Computation Design for Distributed RISs Assisted Probabilistic Semantic Communication in IIoT
In this paper, the problem of spectral-efficient communication and computation resource allocation for distributed reconfigurable intelligent surfaces (RISs) assisted probabilistic semantic communication (PSC) in industrial Internet-of-Things (IIoT) is investigated. In the considered model, multiple RISs are deployed to serve multiple users, while PSC adopts compute-then-transmit protocol to reduce the transmission data size. To support high-rate transmission, the semantic compression ratio, tr…

This https://arxiv.org/abs/2210.17223 has been replaced.
link: https://scholar.google.com/scholar?q=a

Accelerating Distributed MoE Training and Inference with Lina
Scaling model parameters improves model quality at the price of high computation overhead. Sparsely activated models, usually in the form of Mixture of Experts (MoE) architecture, have sub-linear scaling of computation cost with model size, thus providing opportunities to train and serve a larger model at lower cost than their dense counterparts. However, distributed MoE training and inference is inefficient, mainly due to the interleaved all-to-all communication during model computation. This …

Algorithmically Expressive, Always-Terminating Model for Reversible Computation
Matteo PalazzoUniversit\`a di Torino, Luca RoversiUniversit\`a di Torino
https://arxiv.org/abs/2402.19012

Algorithmically Expressive, Always-Terminating Model for Reversible Computation
Concerning classical computational models able to express all the Primitive Recursive Functions (PRF), there are interesting results regarding limits on their algorithmic expressiveness or, equivalently, efficiency, namely the ability to express algorithms with minimal computational cost. By introducing the reversible programming model Forest, at our knowledge, we provide a first study of analogous properties, adapted to the context of reversible computational models that can represent all the …

https://idi.provost.northeastern.edu/the-2024-computation-journalism-symposium/ The 2024 Computation Journalism Symposium will be held this fall in Boston!

Simple inverse kinematics computation considering joint motion efficiency
Ansei Yonezawa, Heisei Yonezawa, Itsuro Kajiwara
https://arxiv.org/abs/2403.20128

Simple inverse kinematics computation considering joint motion efficiency
Inverse kinematics is an important and challenging problem in the operation of industrial manipulators. This study proposes a simple inverse kinematics calculation scheme for an industrial serial manipulator. The proposed technique can calculate appropriate values of the joint variables to realize the desired end-effector position and orientation while considering the motion costs of each joint. Two scalar functions are defined for the joint variables: one is to evaluate the end-effector positi…

This https://arxiv.org/abs/2403.14142 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Unconditional verification of quantum computation with classical light
Verification of quantum computation is a task to efficiently check whether an output given from a quantum computer is correct. Existing verification protocols conducted between a quantum computer to be verified and a verifier necessitate quantum communication to unconditionally detect any malicious behavior of the quantum computer solving any promise problem in ${\sf BQP}$. In this paper, we remove the necessity of the communication of qubits by proposing a "physically-classical" verification p…

Computation-information gap in high-dimensional clustering
Bertrand Even, Christophe Giraud, Nicolas Verzelen
https://arxiv.org/abs/2402.18378 https://

Computation-information gap in high-dimensional clustering
We investigate the existence of a fundamental computation-information gap for the problem of clustering a mixture of isotropic Gaussian in the high-dimensional regime, where the ambient dimension $p$ is larger than the number $n$ of points. The existence of a computation-information gap in a specific Bayesian high-dimensional asymptotic regime has been conjectured by arXiv:1610.02918 based on the replica heuristic from statistical physics. We provide evidence of the existence of such a gap gene…

Copula Approximate Bayesian Computation Using Distribution Random Forests
George Karabatsos
https://arxiv.org/abs/2402.18450 https://…

Copula Approximate Bayesian Computation Using Distribution Random Forests
This paper introduces a novel Approximate Bayesian Computation (ABC) framework for estimating the posterior distribution and the maximum likelihood estimate (MLE) of the parameters of models defined by intractable likelihood functions. This framework can describe the possibly skewed and high dimensional posterior distribution by a novel multivariate copula-based distribution, based on univariate marginal posterior distributions which can account for skewness and be accurately estimated by Distr…

On Efficient Computation of DiRe Committees
Kunal Relia
https://arxiv.org/abs/2402.19365 https://arxiv.org/pdf/2402.19365

On Efficient Computation of DiRe Committees
Consider a committee election consisting of (i) a set of candidates who are divided into arbitrary groups each of size \emph{at most} two and a diversity constraint that stipulates the selection of \emph{at least} one candidate from each group and (ii) a set of voters who are divided into arbitrary populations each approving \emph{at most} two candidates and a representation constraint that stipulates the selection of \emph{at least} one candidate from each population who has a non-null set of …

Alternative paths computation for congestion mitigation in segment-routing networks
S\'ebastien Martin, Youcef Magnouche, Paolo Medagliani, J\'er\'emie Leguay
https://arxiv.org/abs/2404.19314

Alternative paths computation for congestion mitigation in segment-routing networks
In backbone networks, it is fundamental to quickly protect traffic against any unexpected event, such as failures or congestions, which may impact Quality of Service (QoS). Standard solutions based on Segment Routing (SR), such as Topology-Independent Loop-Free Alternate (TI-LFA), are used in practice to handle failures, but no distributed solutions exist for distributed and tactical congestion mitigation. A promising approach leveraging SR has been recently proposed to quickly steer traffic aw…

The thing that irks me is that literally anyone who's using their brain to research the "VR goggles" market for like a day could have told you this.
It has "vanity project" written all over it.
https://mastodon.online/@parismarx/1123389856439290…

@… @… I won't be attending, but am very curious about the topic. I recently spoke with someone from Princeton working on the topic. Was very disappointed to find out it all boils down to computation and formal logic to them. I disagr…

Desencaixei, limpei e organizei todos os meus livros de matemštica (e alguns poucos livros de programação). Deixei uma estante inteira só para esses temas. Infelizmente não houve espaço suficiente para colocar os livros de educação matemštica, problemas de matemštica (inclusive matemštica olímpica), biografias e outras literaturas ligada Š šrea (incluindo obras de divulgação da matemštica para o público leigo). Ficou bem legal a organização por šreas afins, não?

This https://arxiv.org/abs/2310.04542 has been replaced.
link: https://scholar.google.com/scholar?q=a

Lagrangian Duality in Quantum Optimization: Overcoming QUBO Limitations for Constrained Problems
We propose an approach to solving constrained combinatorial optimization problems based on embedding the concept of Lagrangian duality into the framework of adiabatic quantum computation. Within the setting of circuit-model fault-tolerant quantum computation, we demonstrate that this approach achieves a quadratic improvement in circuit depth and maintains a constraint-independent circuit width in contrast to the prevalent approach of solving constrained problems via reformulations based on the …

The Staggering Ecological Impacts of Computation and the Cloud
https://thereader.mitpress.mit.edu/the-staggering-ecological-impacts-of-computation-and-the-cloud/

The Staggering Ecological Impacts of Computation and the Cloud
Anthropologist Steven Gonzalez Monserrate draws on five years of research and ethnographic fieldwork in server farms to illustrate some of the diverse environmental impacts of data storage.

Interesting data, nice visualization here: https://ourworldindata.org/grapher/artificial-intelligence-training-computation

Computation used to train notable artificial intelligence systems
Computation is measured in total petaFLOP, which is 10¹⁵ floating-point operations estimated from AI literature, albeit with some uncertainty. Estimates are expected to be accurate within a factor of 2, or a factor of 5 for recent undisclosed models like GPT-4.

Rapid Computation of the Plasma Dispersion Function: Rational and Multi-pole Approximation, and Improved Accuracy
Huasheng Xie
https://arxiv.org/abs/2404.18719

Rapid Computation of the Plasma Dispersion Function: Rational and Multi-pole Approximation, and Improved Accuracy
The plasma dispersion function $Z(s)$ is a fundamental complex special integral function widely used in the field of plasma physics. The simplest and most rapid, yet accurate, approach to calculating it is through rational or equivalent multi-pole expansions. In this work, we summarize the numerical coefficients that are practically useful to the community. Besides the Pade approximation to obtain coefficients, which are accurate for both small and large arguments, we also employ optimization m…

Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
Wenhan Cao, Wei Pan
https://arxiv.org/abs/2402.17375 https://

Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
Integral reinforcement learning (IntRL) demands the precise computation of the utility function's integral at its policy evaluation (PEV) stage. This is achieved through quadrature rules, which are weighted sums of utility functions evaluated from state samples obtained in discrete time. Our research reveals a critical yet underexplored phenomenon: the choice of the computational method -- in this case, the quadrature rule -- can significantly impact control performance. This impact is traced b…

[2024-02-01 Thu (UTC), no new articles found for cs.CL Computation and Language]

This https://arxiv.org/abs/2404.03147 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Eigenpruning
We introduce eigenpruning, a method that removes singular values from weight matrices in an LLM to improve its performance in a particular task. This method is inspired by interpretability methods designed to automatically find subnetworks of a model which solve a specific task. In our tests, the pruned model outperforms the original model by a large margin, while only requiring minimal computation to prune the weight matrices. In the case of a small synthetic task in integer multiplication, th…

CATSNet: a context-aware network for Height Estimation in a Forested Area based on Pol-TomoSAR data
Wenyu Yang, Sergio Vitale, Hossein Aghababaei, Giampaolo Ferraioli, Vito Pascazio, Gilda Schirinzi
https://arxiv.org/abs/2403.20273

CATSNet: a context-aware network for Height Estimation in a Forested Area based on Pol-TomoSAR data
Tropical forests are a key component of the global carbon cycle. With plans for upcoming space-borne missions like BIOMASS to monitor forestry, several airborne missions, including TropiSAR and AfriSAR campaigns, have been successfully launched and experimented. Typical Synthetic Aperture Radar Tomography (TomoSAR) methods involve complex models with low accuracy and high computation costs. In recent years, deep learning methods have also gained attention in the TomoSAR framework, showing inter…

Qubit encoding for a mixture of localized functions
Taichi Kosugi, Shunsuke Daimon, Hirofumi Nishi, Yu-ichiro Matsushita
https://arxiv.org/abs/2404.18529 h…

Qubit encoding for a mixture of localized functions
One of the crucial generic techniques for quantum computation is the amplitude encoding. Although such techniques have been proposed, each of them often requires exponential classical-computational cost or an oracle whose explicit construction is not provided. Given the recent demands for practical quantum computation, we develop moderately specialized encoding techniques that generate an arbitrary linear combination of localized complex functions. We demonstrate that $n_{\mathrm{loc}}$ discret…

scida: scalable analysis for scientific big data
Chris Byrohl, Dylan Nelson
https://arxiv.org/abs/2402.17818 https://arxiv.org/pdf/24…

scida: scalable analysis for scientific big data
scida is a Python package for reading and analyzing large scientific data sets with support for various cosmological and galaxy formation simulations out-of-the-box. Data access is provided through a hierarchical dictionary-like data structure after a simple load() function. Using the dask library for scalable, parallel and out-of-core computation, all computation requests from a user session are first collected in a task graph. Arbitrary custom analysis, as well as all available dask (array) o…

SEArch: an execution infrastructure for service-based software systems
Carlos G. Lopez Pombo, Pablo Montepagano, Emilio Tuosto
https://arxiv.org/abs/2404.19633

SEArch: an execution infrastructure for service-based software systems
The shift from monolithic applications to composition of distributed software initiated in the early twentieth, is based on the vision of software-as-service. This vision, found in many technologies such as RESTful APIs, advocates globally available services cooperating through an infrastructure providing (access to) distributed computational resources. Choreographies can support this vision by abstracting away local computation and rendering interoperability with message-passing: cooperation i…

This https://arxiv.org/abs/2402.02320 has been replaced.
link: https://scholar.google.com/scholar?q=a

Spin: An Efficient Secure Computation Framework with GPU Acceleration
Accuracy and efficiency remain challenges for multi-party computation (MPC) frameworks. Spin is a GPU-accelerated MPC framework that supports multiple computation parties and a dishonest majority adversarial setup. We propose optimized protocols for non-linear functions that are critical for machine learning, as well as several novel optimizations specific to attention that is the fundamental unit of Transformer models, allowing Spin to perform non-trivial CNNs training and Transformer inferenc…

This https://arxiv.org/abs/2304.14988 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Topology of critical points in boundary matrix duals
Computation of topological charges of the Schwarzschild and charged black holes in AdS in canonical and grand canonical ensembles allows for a classification of the phase transition points via the Bragg-Williams off-shell free energy. We attempt a topological classification of the critical points and the equilibrium phases of the dual gauge theory via a phenomenological matrix model, which captures the features of the ${\cal{N}}=4$, $SU(N)$ Super Yang-Mills theory on $S^3$ at finite temperature…

Distributed computation of temporal twins in periodic undirected time-varying graphs
Lina Azerouk (SU), Binh-Minh Bui-Xuan (NPA, SU, CNRS), Camille Palisoc (SU), Maria Potop-Butucaru (NPA, SU), Massinissa Tighilt (SU, NPA)
https://arxiv.org/abs/2404.17195

Distributed computation of temporal twins in periodic undirected time-varying graphs
Twin nodes in a static network capture the idea of being substitutes for each other for maintaining paths of the same length anywhere in the network. In dynamic networks, we model twin nodes over a time-bounded interval, noted $(Δ,d)$-twins, as follows. A periodic undirected time-varying graph $\mathcal G=(G_t)_{t\in\mathbb N}$ of period $p$ is an infinite sequence of static graphs where $G_t=G_{t+p}$ for every $t\in\mathbb N$. For $Δ$ and $d$ two integers, two distinct nodes $u$ and $v$ in $…

This https://arxiv.org/abs/2402.16328 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIT_…

A Joint Communication and Computation Design for Probabilistic Semantic Communications
In this paper, the problem of joint transmission and computation resource allocation for a multi-user probabilistic semantic communication (PSC) network is investigated. In the considered model, users employ semantic information extraction techniques to compress their large-sized data before transmitting them to a multi-antenna base station (BS). Our model represents large-sized data through substantial knowledge graphs, utilizing shared probability graphs between the users and the BS for effic…

This https://arxiv.org/abs/2307.06016 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csFL_…

Safety and Liveness of Quantitative Properties and Automata
Safety and liveness stand as fundamental concepts in formal languages, playing a key role in verification. The safety-liveness classification of boolean properties characterizes whether a given property can be falsified by observing a finite prefix of an infinite computation trace (always for safety, never for liveness). In the quantitative setting, properties are arbitrary functions from infinite words to partially-ordered domains. Extending this paradigm to the quantitative domain, where prop…

This https://arxiv.org/abs/2305.18334 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration
Conventional multiply-accumulate (MAC) operations have long dominated computation time for deep neural networks (DNNs), espcially convolutional neural networks (CNNs). Recently, product quantization (PQ) has been applied to these workloads, replacing MACs with memory lookups to pre-computed dot products. To better understand the efficiency tradeoffs of product-quantized DNNs (PQ-DNNs), we create a custom hardware accelerator to parallelize and accelerate nearest-neighbor search and dot-product …

Gravitational Waves on Kerr Black Holes I: Reconstruction of Linearized Metric Perturbations
Roman Berens, Trevor Gravely, Alexandru Lupsasca
https://arxiv.org/abs/2403.20311

Gravitational Waves on Kerr Black Holes I: Reconstruction of Linearized Metric Perturbations
The gravitational perturbations of a rotating Kerr black hole are notoriously complicated, even at the linear level. In 1973, Teukolsky showed that their physical degrees of freedom are encoded in two gauge-invariant Weyl curvature scalars that obey a separable wave equation. Determining these scalars is sufficient for many purposes, such as the computation of energy fluxes. However, some applications -- such as second-order perturbation theory -- require the reconstruction of metric perturbati…

This https://arxiv.org/abs/2311.06717 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Whitehead Filtrations for Computations in Topological Hochschild Homology
We discuss spectral sequences coming from Whitehead filtrations in the computation of topological Hochschild homology of ring spectra. Using cyclic invariance, this makes for simple computations of $THH$ of connective rings $R$ with coefficients in discrete ring spectra. In particular, we show how to use this to compute $THH(tmf,\mathbb{F}_2)$, and $THH(tmf,\mathbb{Z}_{(2)})$, where $tmf$ denotes the $\mathbb{E}_\infty$ ring spectrum of topological modular forms. Then, we obtain a description o…

This https://arxiv.org/abs/2309.02645 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Mean Field Game-based Waveform Precoding Design for Mobile Crowd Integrated Sensing, Communication, and Computation Systems
Data collection and processing timely is crucial for mobile crowd integrated sensing, communication, and computation~(ISCC) systems with various applications such as smart home and connected cars, which requires numerous integrated sensing and communication~(ISAC) devices to sense the targets and offload the data to the base station~(BS) for further processing. However, as the number of ISAC devices growing, there exists intensive interactions among ISAC devices in the processes of data collect…

SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networks
Sreyes Venkatesh, Razvan Marinescu, Jason K. Eshraghian
https://arxiv.org/abs/2404.19668

SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networks
Weight quantization is used to deploy high-performance deep learning models on resource-limited hardware, enabling the use of low-precision integers for storage and computation. Spiking neural networks (SNNs) share the goal of enhancing efficiency, but adopt an 'event-driven' approach to reduce the power consumption of neural network inference. While extensive research has focused on weight quantization, quantization-aware training (QAT), and their application to SNNs, the precision reduction o…

Constrained maximization of conformal capacity
Harri Hakula, Mohamed M. S. Nasser, Matti Vuorinen
https://arxiv.org/abs/2404.19663 https://arxiv.org/pdf/2404.19663
arXiv:2404.19663v1 Announce Type: new
Abstract: We consider constellations of disks which are unions of disjoint hyperbolic disks in the unit disk with fixed radii and unfixed centers. We study the problem of maximizing the conformal capacity of a constellation under constraints on the centers in two cases. In the first case the constraint is that the centers are at most at distance $R \in(0,1)$ from the origin and in the second case it is required that the centers are on the subsegment $[-R,R]$ of a diameter of the unit disk. We study also similar types of constellations with hyperbolic segments instead of the hyperbolic disks. Our computational experiments suggest that a dispersion phenomenon occurs: the disks/segments go as close to the unit circle as possible under these constraints and stay as far as possible from each other. The computation of capacity reduces to the Dirichlet problem for the Laplace equation which we solve with a fast boundary integral equation method. The results are double-checked with the $hp$-FEM method.

[2024-04-30 Tue (UTC), 1 new article found for cs.SC Symbolic Computation]

SPLICE -- Streamlining Digital Pathology Image Processing
Areej Alsaafin, Peyman Nejat, Abubakr Shafique, Jibran Khan, Saghir Alfasly, Ghazal Alabtah, H. R. Tizhoosh
https://arxiv.org/abs/2404.17704 https://arxiv.org/pdf/2404.17704
arXiv:2404.17704v1 Announce Type: new
Abstract: Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whole Slide Images (WSIs), there's a growing demand for efficient retrieval, processing, and analysis of relevant images from vast biomedical archives. However, processing WSIs presents challenges due to their large size and content complexity. Full computer digestion of WSIs is impractical, and processing all patches individually is prohibitively expensive. In this paper, we propose an unsupervised patching algorithm, Sequential Patching Lattice for Image Classification and Enquiry (SPLICE). This novel approach condenses a histopathology WSI into a compact set of representative patches, forming a "collage" of WSI while minimizing redundancy. SPLICE prioritizes patch quality and uniqueness by sequentially analyzing a WSI and selecting non-redundant representative features. We evaluated SPLICE for search and match applications, demonstrating improved accuracy, reduced computation time, and storage requirements compared to existing state-of-the-art methods. As an unsupervised method, SPLICE effectively reduces storage requirements for representing tissue images by 50%. This reduction enables numerous algorithms in computational pathology to operate much more efficiently, paving the way for accelerated adoption of digital pathology.

Ab initio computation of Auger decay in heavy metals: zinc about it
Anthuan Ferino-P\'erez, Thomas-C. Jagau
https://arxiv.org/abs/2402.18730 https://…

Ab initio computation of Auger decay in heavy metals: zinc about it
We report the first coupled-cluster study of Auger decay in heavy metals. The zinc atom is used as a case study due to its relevance to the Auger emission properties of the $^{67}$Ga radionuclide. Coupled-cluster theory combined with complex basis functions is used to describe the transient nature of the core-ionized zinc atom. We also introduce second-order Møller-Plesset perturbation theory as an alternative method for computing partial Auger decay widths. Scalar-relativistic effects are inc…

Low-Rank Online Dynamic Assortment with Dual Contextual Information
Seong Jin Lee, Will Wei Sun, Yufeng Liu
https://arxiv.org/abs/2404.17592 https://

Low-Rank Online Dynamic Assortment with Dual Contextual Information
As e-commerce expands, delivering real-time personalized recommendations from vast catalogs poses a critical challenge for retail platforms. Maximizing revenue requires careful consideration of both individual customer characteristics and available item features to optimize assortments over time. In this paper, we consider the dynamic assortment problem with dual contexts -- user and item features. In high-dimensional scenarios, the quadratic growth of dimensions complicates computation and est…

Efficient, robust and universal computation of classical orbital elements
Roberto Flores, Elena Fantino
https://arxiv.org/abs/2404.18141 https://

Efficient, robust and universal computation of classical orbital elements
This paper reviews the standard algorithm for converting spacecraft state vectors to Keplerian orbital elements with a focus on its computer implementation. It analyzes the shortcomings of the scheme as described in the literature, and proposes changes to address orbits of arbitrary eccentricity and inclination in a robust way. Next, it presents two alternative schemes that simplify the program structure while improving the accuracy and speed of the transformation on modern computer architectur…

Is the edge really necessary for drone computing offloading? An experimental assessment in carrier-grade 5G operator networks
David Candal-Ventureira, Francisco Javier Gonz\'alez-Casta\~no, Felipe Gil-Casti\~neira, Pablo Fondo-Ferreiro
https://arxiv.org/abs/2403.19729

Is the edge really necessary for drone computing offloading? An experimental assessment in carrier-grade 5G operator networks
In this article, we evaluate the first experience of computation offloading from drones to real fifth-generation (5G) operator systems, including commercial and private carrier-grade 5G networks. A follow-me drone service was implemented as a representative testbed of remote video analytics. In this application, an image of a person from a drone camera is processed at the edge, and image tracking displacements are translated into positioning commands that are sent back to the drone, so that the…

This https://arxiv.org/abs/2202.12287 has been replaced.
link: https://scholar.google.com/scholar?q=a

Davydov-Yetter cohomology and relative homological algebra
Davydov--Yetter (DY) cohomology classifies infinitesimal deformations of the monoidal structure of tensor functors and tensor categories. In this paper we provide new tools for the computation of the DY cohomology for finite tensor categories and exact functors between them. The key point is to realize DY cohomology as relative Ext groups. In particular, we prove that the infinitesimal deformations of a tensor category $\mathcal{C}$ are classified by the 3-rd self-extension group of the tensor …

Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games
Gabriele Farina, Charilaos Pipis
https://arxiv.org/abs/2402.16316 https://

Polynomial-Time Computation of Exact $Φ$-Equilibria in Polyhedral Games
It is a well-known fact that correlated equilibria can be computed in polynomial time in a large class of concisely represented games using the celebrated Ellipsoid Against Hope algorithm (Papadimitriou and Roughgarden, 2008; Jiang and Leyton-Brown, 2015). However, the landscape of efficiently computable equilibria in sequential (extensive-form) games remains unknown. The Ellipsoid Against Hope does not apply directly to these games, because they do not have the required "polynomial type" prope…

Mass action systems: two criteria for Hopf bifurcation without Hurwitz
Nicola Vassena
https://arxiv.org/abs/2402.18188 https://arxiv.…

Mass action systems: two criteria for Hopf bifurcation without Hurwitz
We state two sufficient criteria for periodic oscillations in mass action systems. Neither criterion requires a computation of the Hurwitz determinants. The first criterion also applies to general kinetics and it concerns fully-open systems: in essence, it guarantees periodic oscillations whenever the system admits a steady state with a simple pair of complex conjugate eigenvalues with positive real part. The second criterion states an algebraic condition based on the steady-state Jacobian matr…

Computation of the expectation value of the spin operator $\hat{S}^2$ for the Spin-Flip Bethe-Salpeter Equation
Bradford A. Barker, Arabi Seshappan, David A. Strubbe
https://arxiv.org/abs/2402.17719

Computation of the expectation value of the spin operator $\hat{S}^2$ for the Spin-Flip Bethe-Salpeter Equation
Spin-flip methods applied to excited-state approaches like the Bethe-Salpeter Equation allow access to the excitation energies of open-shell systems, such as molecules and defects in solids. The eigenstates of these solutions, however, are generally not eigenstates of the spin operator $\hat{S}^2$. Even for simple cases where the excitation vector is expected to be, for example, a triplet state, the value of $\langle \hat{S}^2 \rangle$ may be found to differ from 2.00; this difference is called…

This https://arxiv.org/abs/2302.12877 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Rigorous computation of solutions of semi-linear PDEs on unbounded domains via spectral methods
In this article we present a general method to rigorously prove existence of strong solutions to a large class of autonomous semi-linear PDEs in a Hilbert space $H^{l}\subset H^{s}(\mathbb{R}^{m})$ ($s\geq1$) via computer-assisted proofs. Our approach is fully spectral and uses Fourier series to approximate functions in $H^{l}$ as well as bounded linear operators from $L^{2}$ to $H^{l}$. In particular, we construct approximate inverses of differential operators via Fourier series approximations…

This https://arxiv.org/abs/2307.05590 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Efficient Computation of Magnetic Polarizability Tensor Spectral Signatures for Object Characterisation in Metal Detection
Purpose: Magnetic polarizability tensors (MPTs) provide an economical characterisation of conducting magnetic metallic objects and their spectral signature can aid in the solution of metal detection inverse problems, such as scrap metal sorting, searching for unexploded ordnance in areas of former conflict, and security screening at event venues and transport hubs. In this work, the authors discuss methods for efficiently building large dictionaries for classification approaches. Design/methodo…

This https://arxiv.org/abs/2404.10255 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Privacy-Preserving Training-as-a-Service for On-Device Intelligence: Concept, Architectural Scheme, and Open Problems
On-device intelligence (ODI) enables artificial intelligence (AI) applications to run on end devices, providing real-time and customized AI services without relying on remote servers. However, training models for on-device deployment face significant challenges due to the decentralized and privacy-sensitive nature of users' data, along with end-side constraints related to network connectivity, computation efficiency, etc. Existing training paradigms, such as cloud-based training, federated lear…

Graphics Processing Unit/Artificial Neural Network-accelerated large-eddy simulation of turbulent combustion: Application to swirling premixed flames
Min Zhang, Runze Mao, Han Li, Zhenhua An, Zhi X. Chen
https://arxiv.org/abs/2402.18858

Graphics Processing Unit/Artificial Neural Network-accelerated large-eddy simulation of turbulent combustion: Application to swirling premixed flames
Within the scope of reacting flow simulations, the real-time direct integration (DI) of stiff ordinary differential equations (ODE) for the computation of chemical kinetics stands as the primary demand on computational resources. Meanwhile, as the number of transport equations that need to be solved increases, the computational cost grows more substantially, particularly for those combustion models involving direct coupling of chemistry and flow such as the transported probability density funct…

Differentiable Geodesic Distance for Intrinsic Minimization on Triangle Meshes
Yue Li, Logan Numerow, Bernhard Thomaszewski, Stelian Coros
https://arxiv.org/abs/2404.18610

Differentiable Geodesic Distance for Intrinsic Minimization on Triangle Meshes
Computing intrinsic distances on discrete surfaces is at the heart of many minimization problems in geometry processing and beyond. Solving these problems is extremely challenging as it demands the computation of on-surface distances along with their derivatives. We present a novel approach for intrinsic minimization of distance-based objectives defined on triangle meshes. Using a variational formulation of shortest-path geodesics, we compute first and second-order distance derivatives based on…

AI Consciousness is Inevitable: A Theoretical Computer Science Perspective
Lenore Blum, Manuel Blum
https://arxiv.org/abs/2403.17101 https://

AI Consciousness is Inevitable: A Theoretical Computer Science Perspective
We look at consciousness through the lens of Theoretical Computer Science, a branch of mathematics that studies computation under resource limitations. From this perspective, we develop a formal machine model for consciousness. The model is inspired by Alan Turing's simple yet powerful model of computation and Bernard Baars' theater model of consciousness. Though extremely simple, the model aligns at a high level with many of the major scientific theories of human and animal consciousness, supp…

Analytical computation of bifurcation of orbits near collinear libration point in the restricted three-body problem
Mingpei Lin, Tong Luo, Hayato Chiba
https://arxiv.org/abs/2403.18237

Analytical computation of bifurcation of orbits near collinear libration point in the restricted three-body problem
A unified analytical solution is presented for constructing the phase space near collinear libration points in the Circular Restricted Three-body Problem (CRTBP), encompassing Lissajous orbits and quasihalo orbits, their invariant manifolds, as well as transit and non-transit orbits. Traditional methods could only derive separate analytical solutions for the invariant manifolds of Lissajous orbits and halo orbits, falling short for the invariant manifolds of quasihalo orbits. By introducing a c…

This https://arxiv.org/abs/2305.08460 has been replaced.
link: https://scholar.google.com/scholar?q=a

Selective Population Protocols
The model of population protocols provides a universal platform to study distributed processes driven by pairwise interactions of anonymous agents. While population protocols present an elegant and robust model for randomized distributed computation, their efficiency wanes when tackling issues that require more focused communication or the execution of multiple processes. To address this issue, we propose a new, selective variant of population protocols by introducing a partition of the state s…

This https://arxiv.org/abs/2312.13344 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Improving the five-point bootstrap
We present a new algorithm for the numerical evaluation of five-point conformal blocks in $d$-dimensions, greatly improving the efficiency of their computation. To do this we use an appropriate ansatz for the blocks as a series expansion in radial coordinates, derive a set of recursion relations for the unknown coefficients in the ansatz, and evaluate the series using a Padé approximant to accelerate its convergence. We then study the $\langleσσεσσ\rangle$ correlator in the 3d critical Is…

This https://arxiv.org/abs/2207.13261 has been replaced.
link: https://scholar.google.com/scholar?q=a

On Error Correction for Nonvolatile Processing-In-Memory
Processing in memory (PiM) represents a promising computing paradigm to enhance performance of numerous data-intensive applications. Variants performing computing directly in emerging nonvolatile memories can deliver very high energy efficiency. PiM architectures directly inherit the vulnerabilities of the underlying memory substrates, but they also are subject to errors due to the computation in place. Numerous well-established error correcting codes (ECC) for memory exist, and are also consid…

This https://arxiv.org/abs/2403.15294 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Nonlinear Reachable Set Computation and Model Predictive Control for Safe Hypersonic Re-entry of Atmospheric Vehicles
This paper investigates the application of reachability analysis to the re-entry problem faced by vehicles entering Earth's atmosphere. The study delves into the time evolution of reachable sets for the system, particularly when subject to nonlinear implicit controls, given the potential damage from the intense heat generated during hypersonic re-entry. Our proposed methodology leverages zonotopes and constrained zonotopes to ensure compliance with safety specifications. Furthermore, we utilize…

This https://arxiv.org/abs/2401.10638 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

Accurately Computing Expected Visiting Times and Stationary Distributions in Markov Chains
We study the accurate and efficient computation of the expected number of times each state is visited in discrete- and continuous-time Markov chains. To obtain sound accuracy guarantees efficiently, we lift interval iteration and topological approaches known from the computation of reachability probabilities and expected rewards. We further study applications of expected visiting times, including the sound computation of the stationary distribution and expected rewards conditioned on reaching m…

This https://arxiv.org/abs/2312.05248 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Topology-Based Reconstruction Prevention for Decentralised Learning
Decentralised learning has recently gained traction as an alternative to federated learning in which both data and coordination are distributed over its users. To preserve data confidentiality, decentralised learning relies on differential privacy, multi-party computation, or a combination thereof. However, running multiple privacy-preserving summations in sequence may allow adversaries to perform reconstruction attacks. Unfortunately, current reconstruction countermeasures either cannot trivia…

This https://arxiv.org/abs/2311.09393 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csPL_…

Taypsi: Static Enforcement of Privacy Policies for Policy-Agnostic Oblivious Computation
Secure multiparty computation (MPC) techniques enable multiple parties to compute joint functions over their private data without sharing that data to other parties, typically by employing powerful cryptographic protocols to protect individual's data. One challenge when writing such functions is that most MPC languages force users to intermix programmatic and privacy concerns in a single application, making it difficult to change or audit a program's underlying privacy policy. Existing policy-a…

Computation Rate Maximization for Wireless Powered Edge Computing With Multi-User Cooperation
Yang Li, Xing Zhang, Bo Lei, Qianying Zhao, Min Wei, Zheyan Qu, Wenbo Wang
https://arxiv.org/abs/2402.16866

Computation Rate Maximization for Wireless Powered Edge Computing With Multi-User Cooperation
The combination of mobile edge computing (MEC) and radio frequency-based wireless power transfer (WPT) presents a promising technique for providing sustainable energy supply and computing services at the network edge. This study considers a wireless-powered mobile edge computing system that includes a hybrid access point (HAP) equipped with a computing unit and multiple Internet of Things (IoT) devices. In particular, we propose a novel muti-user cooperation scheme to improve computation perfor…

This https://arxiv.org/abs/2305.18334 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAR_…

PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration
Conventional multiply-accumulate (MAC) operations have long dominated computation time for deep neural networks (DNNs), espcially convolutional neural networks (CNNs). Recently, product quantization (PQ) has been applied to these workloads, replacing MACs with memory lookups to pre-computed dot products. To better understand the efficiency tradeoffs of product-quantized DNNs (PQ-DNNs), we create a custom hardware accelerator to parallelize and accelerate nearest-neighbor search and dot-product …

This https://arxiv.org/abs/2302.09597 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Solving Differential-Algebraic Equations in Power System Dynamic Analysis with Quantum Computing
Power system dynamics are generally modeled by high dimensional nonlinear differential-algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for po…

Extending Llama-3's Context Ten-Fold Overnight
Peitian Zhang, Ninglu Shao, Zheng Liu, Shitao Xiao, Hongjin Qian, Qiwei Ye, Zhicheng Dou
https://arxiv.org/abs/2404.19553 https://arxiv.org/pdf/2404.19553
arXiv:2404.19553v1 Announce Type: new
Abstract: We extend the context length of Llama-3-8B-Instruct from 8K to 80K via QLoRA fine-tuning. The entire training cycle is super efficient, which takes 8 hours on one 8xA800 (80G) GPU machine. The resulted model exhibits superior performances across a broad range of evaluation tasks, such as NIHS, topic retrieval, and long-context language understanding; meanwhile, it also well preserves the original capability over short contexts. The dramatic context extension is mainly attributed to merely 3.5K synthetic training samples generated by GPT-4 , which indicates the LLMs' inherent (yet largely underestimated) potential to extend its original context length. In fact, the context length could be extended far beyond 80K with more computation resources. Therefore, the team will publicly release the entire resources (including data, model, data generation pipeline, training code) so as to facilitate the future research from the community: \url{https://github.com/FlagOpen/FlagEmbedding}.

[2024-05-01 Wed (UTC), 1 new article found for cs.SC Symbolic Computation]

Semi-device independent characterization of multiphoton indistinguishability
Giovanni Rodari, Leonardo Novo, Riccardo Albiero, Alessia Suprano, Carlos T. Tavares, Eugenio Caruccio, Francesco Hoch, Taira Giordani, Gonzalo Carvacho, Marco Gardina, Niki Di Giano, Serena Di Giorgio, Giacomo Corrielli, Francesco Ceccarelli, Roberto Osellame, Nicol\`o Spagnolo, Ernesto F. Galv\~ao, Fabio Sciarrino

Semi-device independent characterization of multiphoton indistinguishability
Multiphoton indistinguishability is a central resource for quantum enhancement in sensing and computation. Developing and certifying large scale photonic devices requires reliable and accurate characterization of this resource, preferably using methods that are robust against experimental errors. Here, we propose a set of methods for the characterization of multiphoton indistinguishability, based on measurements of bunching and photon number variance. Our methods are robust in a semi-device ind…

This https://arxiv.org/abs/2402.11743 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Hybrid Online-Offline Learning for Task Offloading in Mobile Edge Computing Systems
We consider a multi-user multi-server mobile edge computing (MEC) system, in which users arrive on a network randomly over time and generate computation tasks, which will be computed either locally on their own computing devices or be offloaded to one of the MEC servers. Under such a dynamic network environment, we propose a novel task offloading policy based on hybrid online-offline learning, which can efficiently reduce the overall computation delay and energy consumption only with informatio…

Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrovi\'c
https://arxiv.org/abs/2402.15668

Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
Given a graph with positive and negative edge labels, the correlation clustering problem aims to cluster the nodes so to minimize the total number of between-cluster positive and within-cluster negative edges. This problem has many applications in data mining, particularly in unsupervised learning. Inspired by the prevalence of large graphs and constantly changing data in modern applications, we study correlation clustering in dynamic, parallel (MPC), and local computation (LCA) settings. We de…

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction
K. Aditya Mohan, Massimiliano Ferrucci, Chuck Divin, Garrett A. Stevenson, Hyojin Kim
https://arxiv.org/abs/2404.19075 https://arxiv.org/pdf/2404.19075
arXiv:2404.19075v1 Announce Type: new
Abstract: 4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an extremely ill-posed inverse problem. Existing approaches assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. We use a continuous time and space forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued object coordinates. Unlike existing state-of-the-art neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions even for extremely large CT data sizes. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

X-ResQ: Reverse Annealing for Quantum MIMO Detection with Flexible Parallelism
Minsung Kim, Abhishek Kumar Singh, Davide Venturelli, John Kaewell, Kyle Jamieson
https://arxiv.org/abs/2402.18778

X-ResQ: Reverse Annealing for Quantum MIMO Detection with Flexible Parallelism
Quantum Annealing (QA)-accelerated MIMO detection is an emerging research approach in the context of NextG wireless networks. The opportunity is to enable large MIMO systems and thus improve wireless performance. The approach aims to leverage QA to expedite the computation required for theoretically optimal but computationally-demanding Maximum Likelihood detection to overcome the limitations of the currently deployed linear detectors. This paper presents \textbf{X-ResQ}, a QA-based MIMO detect…

This https://arxiv.org/abs/2401.08614 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Computing the Haar state of $\mathcal{O}(SL_q(3))$ using value preserving (anti)homomorphisms
In this paper, we introduce two (anti)homomorphisms that preserve the Haar state values of monomials. Together with the modular automorphism, the three (anti)homomorphisms are used in our new algorithm to compute the Haar states of monomials on $\mathcal{O}(SL_q(3))$. Comparing with the algorithm proposed in the author's previous work \cite{lu2023}, the new algorithm reduces the linear relations used in the computation to a half.

PWEXP: An R Package Using Piecewise Exponential Model for Study Design and Event/Timeline Prediction
Tianchen Xu, Rachael Wen
https://arxiv.org/abs/2404.17772

PWEXP: An R Package Using Piecewise Exponential Model for Study Design and Event/Timeline Prediction
Parametric assumptions such as exponential distribution are commonly used in clinical trial design and analysis. However, violation of distribution assumptions can introduce biases in sample size and power calculations. Piecewise exponential (PWE) hazard model partitions the hazard function into segments each with constant hazards and is easy for interpretation and computation. Due to its piecewise property, PWE can fit a wide range of survival curves and accurately predict the future number of…

This https://arxiv.org/abs/2309.15059 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

An Elliptic One-Loop Amplitude in Anti-de-Sitter Space
We present full analytic results for the four-point one-loop amplitude of a conformally coupled scalar in four-dimensional Anti-de-Sitter space dual to a primary operator with scaling dimension 1. The computation is based on an intriguing recent discovery, connecting Witten diagrams and flat-space Feynman integrals, which led to an expression of the amplitude of interest as a pure combination of single-valued multiple polylogarithms and an integral which cannot be reduced to multiple polylogari…

This https://arxiv.org/abs/2401.06125 has been replaced.
link: https://scholar.google.com/scholar?q=a

Improved Capacity Outer Bound for Private Quadratic Monomial Computation
In private computation, a user wishes to retrieve a function evaluation of messages stored on a set of databases without revealing the function's identity to the databases. Obead \emph{et al.} introduced a capacity outer bound for private nonlinear computation, dependent on the order of the candidate functions. Focusing on private \emph{quadratic monomial} computation, we propose three methods for ordering candidate functions: a graph edge-coloring method, a graph-distance method, and an entrop…

Equivalence Checking of Parameterised Quantum Circuits
Xin Hong, Wei-Jia Huang, Wei-Chen Chien, Yuan Feng, Min-Hsiu Hsieh, Sanjiang Li, Mingsheng Ying
https://arxiv.org/abs/2404.18456

Equivalence Checking of Parameterised Quantum Circuits
Parameterised quantum circuits (PQCs) hold great promise for demonstrating quantum advantages in practical applications of quantum computation. Examples of successful applications include the variational quantum eigensolver, the quantum approximate optimisation algorithm, and quantum machine learning. However, before executing PQCs on real quantum devices, they undergo compilation and optimisation procedures. Given the inherent error-proneness of these processes, it becomes crucial to verify th…

This https://arxiv.org/abs/2305.11469 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

(Rectified Version) The Barzilai-Borwein Method for Distributed Optimization over Unbalanced Directed Networks
This paper studies optimization problems over multi-agent systems, in which all agents cooperatively minimize a global objective function expressed as a sum of local cost functions. Each agent in the systems uses only local computation and communication in the overall process without leaking their private information. Based on the Barzilai-Borwein (BB) method and multi-consensus inner loops, a distributed algorithm with the availability of larger stepsizes and accelerated convergence, namely AD…

Numerical simulation of resistance furnaces by using distributed and lumped models
A. Berm\'udez, D. G\'omez, D. Gonz\'alez-Pe\~nas
https://arxiv.org/abs/2402.18232

Numerical simulation of resistance furnaces by using distributed and lumped models
This work proposes a methodology combining distributed and lumped models to simulate the current distribution in an indirect heat resistance furnace and, in particular, to compute the current to be supplied in order to obtain a desired power. The distributed model is a time-harmonic eddy current problem which has been numerically solved by using a finite element method. The lumped model is based on the computation of a reduced impedance associated to an equivalent circuit model. The effectivene…

[2024-04-01 Mon (UTC), no new articles found for cs.SC Symbolic Computation]

OzMAC: An Energy-Efficient Sparsity-Exploiting Multiply-Accumulate-Unit Design for DL Inference
Harideep Nair, Prabhu Vellaisamy, Tsung-Han Lin, Perry Wang, Shawn Blanton, John Paul Shen
https://arxiv.org/abs/2402.19376

OzMAC: An Energy-Efficient Sparsity-Exploiting Multiply-Accumulate-Unit Design for DL Inference
General Matrix Multiply (GEMM) hardware, employing large arrays of multiply-accumulate (MAC) units, perform bulk of the computation in deep learning (DL). Recent trends have established 8-bit integer (INT8) as the most widely used precision for DL inference. This paper proposes a novel MAC design capable of dynamically exploiting bit sparsity (i.e., number of `0' bits within a binary value) in input data to achieve significant improvements on area, power and energy. The proposed architecture, c…

KGAMC: A Novel Knowledge Graph Driven Automatic Modulation Classification Scheme
ike Li, Lu Yua, Fuhui Zhou, Qihui Wu, Naofal Al-Dhahir, Kai-Kit Wong
https://arxiv.org/abs/2402.19188

KGAMC: A Novel Knowledge Graph Driven Automatic Modulation Classification Scheme
Automatic modulation classification (AMC) is a promising technology to realize intelligent wireless communications in the sixth generation (6G) wireless communication networks. Recently, many data-and-knowledge dual-driven AMC schemes have achieved high accuracy. However, most of these schemes focus on generating additional prior knowledge or features of blind signals, which consumes longer computation time and ignores the interpretability of the model learning process. To solve these problems,…

Efficient quaternion CUR method for low-rank approximation to quaternion matrix
Peng-Ling Wu, Kit Ian Kou, Hongmin Cai, Zhaoyuan Yu
https://arxiv.org/abs/2402.19147

Efficient quaternion CUR method for low-rank approximation to quaternion matrix
The low-rank quaternion matrix approximation has been successfully applied in many applications involving signal processing and color image processing. However, the cost of quaternion models for generating low-rank quaternion matrix approximation is sometimes considerable due to the computation of the quaternion singular value decomposition (QSVD), which limits their application to real large-scale data. To address this deficiency, an efficient quaternion matrix CUR (QMCUR) method for low-rank …

This https://arxiv.org/abs/2303.10289 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNI_…

Play to Earn in the Metaverse with Mobile Edge Computing over Wireless Networks: A Deep Reinforcement Learning Approach
The Metaverse play-to-earn games have been gaining popularity as they enable players to earn in-game tokens which can be translated to real-world profits. With the advancements in augmented reality (AR) technologies, users can play AR games in the Metaverse. However, these high-resolution games are compute-intensive, and in-game graphical scenes need to be offloaded from mobile devices to an edge server for computation. In this work, we consider an optimization problem where the Metaverse Servi…

Probabilistic Interval Analysis of Unreliable Programs
Dibyendu Das, Soumyajit Dey
https://arxiv.org/abs/2404.16997 https://arxiv.org…

Probabilistic Interval Analysis of Unreliable Programs
Advancement of chip technology will make future computer chips faster. Power consumption of such chips shall also decrease. But this speed gain shall not come free of cost, there is going to be a trade-off between speed and efficiency, i.e accuracy of the computation. In order to achieve this extra speed we will simply have to let our computers make more mistakes in computations. Consequently, systems built with these type of chips will possess an innate unreliability lying within. Programs wri…

Oscillations-Aware Frequency Security Assessment via Efficient Worst-Case Frequency Nadir Computation
Yan Jiang, Hancheng Min, Baosen Zhang
https://arxiv.org/abs/2402.16765

Oscillations-Aware Frequency Security Assessment via Efficient Worst-Case Frequency Nadir Computation
Frequency security assessment following major disturbances has long been one of the central tasks in power system operations. The standard approach is to study the center of inertia frequency, an aggregate signal for an entire system, to avoid analyzing the frequency signal at individual buses. However, as the amount of low-inertia renewable resources in a grid increases, the center of inertia frequency is becoming too coarse to provide reliable frequency security assessment. In this paper, we …

This https://arxiv.org/abs/2305.06942 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Optimizing Distributed ML Communication with Fused Computation-Collective Operations
In order to satisfy their ever increasing capacity and compute requirements, machine learning models are distributed across multiple nodes using numerous parallelism strategies. As a result, collective communications are often on the critical path, and hiding their latency by overlapping kernel-granular communication and computation is difficult due to the absence of independent computation. In this work, we propose fusing computation with dependent collective communication by leveraging GPUs' …

[2024-03-01 Fri (UTC), no new articles found for cs.SC Symbolic Computation]

Functionally-Complete Boolean Logic in Real DRAM Chips: Experimental Characterization and Analysis
Ismail Emir Yuksel, Yahya Can Tugrul, Ataberk Olgun, F. Nisa Bostanci, A. Giray Yaglikci, Geraldo F. Oliveira, Haocong Luo, Juan G\'omez-Luna, Mohammad Sadrosadati, Onur Mutlu
https://arxiv.org/abs/2402.18736

Functionally-Complete Boolean Logic in Real DRAM Chips: Experimental Characterization and Analysis
Processing-using-DRAM (PuD) is an emerging paradigm that leverages the analog operational properties of DRAM circuitry to enable massively parallel in-DRAM computation. PuD has the potential to significantly reduce or eliminate costly data movement between processing elements and main memory. Prior works experimentally demonstrate three-input MAJ (i.e., MAJ3) and two-input AND and OR operations in commercial off-the-shelf (COTS) DRAM chips. Yet, demonstrations on COTS DRAM chips do not provide …

Numerical simulation of resistance furnaces by using distributed and lumped models
A. Berm\'udez, D. G\'omez, D. Gonz\'alez-Pe\~nas
https://arxiv.org/abs/2402.18232

Numerical simulation of resistance furnaces by using distributed and lumped models
This work proposes a methodology combining distributed and lumped models to simulate the current distribution in an indirect heat resistance furnace and, in particular, to compute the current to be supplied in order to obtain a desired power. The distributed model is a time-harmonic eddy current problem which has been numerically solved by using a finite element method. The lumped model is based on the computation of a reduced impedance associated to an equivalent circuit model. The effectivene…

Distributed Swarm Learning for Edge Internet of Things
Yue Wang, Zhi Tian, FXin Fan, Zhipeng Cai, Cameron Nowzari, Kai Zeng
https://arxiv.org/abs/2403.20188

Distributed Swarm Learning for Edge Internet of Things
The rapid growth of Internet of Things (IoT) has led to the widespread deployment of smart IoT devices at wireless edge for collaborative machine learning tasks, ushering in a new era of edge learning. With a huge number of hardware-constrained IoT devices operating in resource-limited wireless networks, edge learning encounters substantial challenges, including communication and computation bottlenecks, device and data heterogeneity, security risks, privacy leakages, non-convex optimization, a…

On Central Primitives for Quantum Cryptography with Classical Communication
Kai-Min Chung, Eli Goldin, Matthew Gray
https://arxiv.org/abs/2402.17715 https:…

On Central Primitives for Quantum Cryptography with Classical Communication
Recent work has introduced the "Quantum-Computation Classical-Communication" (QCCC) (Chung et. al.) setting for cryptography. There has been some evidence that One Way Puzzles (OWPuzz) are the natural central cryptographic primitive for this setting (Khurana and Tomer). For a primitive to be considered central it should have several characteristics. It should be well behaved (which for this paper we will think of as having amplification, combiners, and universal constructions); it should be imp…

[2024-02-29 Thu (UTC), no new articles found for cs.SC Symbolic Computation]

[2024-02-01 Thu (UTC), no new articles found for cs.SC Symbolic Computation]

A Novel Channel Coding Scheme for Digital Multiple Access Computing
Xiaojing Yan, Saeed Razavikia, Carlo Fischione
https://arxiv.org/abs/2404.16476 https:/…

A Novel Channel Coding Scheme for Digital Multiple Access Computing
In this paper, we consider the ChannelComp framework, which facilitates the computation of desired functions by multiple transmitters over a common receiver using digital modulations across a multiple access channel. While ChannelComp currently offers a broad framework for computation by designing digital constellations for over-the-air computation and employing symbol-level encoding, encoding the repeated transmissions of the same symbol and using the corresponding received sequence may signif…

This https://arxiv.org/abs/2402.14788 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Expectation Values of Conserved Charges in Integrable Quantum Field Theories out of Thermal Equilibrium
In this work we present a computation of the averages of conserved charge densities and currents of (1+1)-dimensional Integrable Quantum Field Theories in Generalised Gibbs Ensembles. Our approach is based on the quasi-particle description provided by the Thermodynamic Bethe Ansatz combined with the principles of Generalised Hydrodynamics, and we focus on Non-Equilibrium Steady State averages. When considering the ultraviolet (i.e. high temperature) limit of such averages, we recover the famous…

This https://arxiv.org/abs/2307.10147 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Tangling schedules eases hardware connectivity requirements for quantum error correction
Quantum computers have the potential to change the way we solve computational problems. Due to the noisy nature of qubits, the need arises to correct physical errors occurring during computation. The surface code is a promising candidate for such error correction that shows high threshold and which can store a logical quantum state on hardware with square-grid connectivity, a type of device that already exists. However, for logical quantum computation, the measurement of some irregular, non-loc…

Delay-Optimal Forwarding and Computation Offloading for Service Chain Tasks
Jinkun Zhang, Yuezhou Liu, Edmund Yeh
https://arxiv.org/abs/2403.15936 https://…

Delay-Optimal Forwarding and Computation Offloading for Service Chain Tasks
Emerging edge computing paradigms enable heterogeneous devices to collaborate on complex computation applications. However, for congestible links and computing units, delay-optimal forwarding and offloading for service chain tasks (e.g., DNN with vertical split) in edge computing networks remains an open problem. In this paper, we formulate the service chain forwarding and offloading problem with arbitrary topology and heterogeneous transmission/computation capability, and aim to minimize the a…

A Novel Channel Coding Scheme for Digital Multiple Access Computing
Xiaojing Yan, Saeed Razavikia, Carlo Fischione
https://arxiv.org/abs/2404.16476 https:/…

A Novel Channel Coding Scheme for Digital Multiple Access Computing
In this paper, we consider the ChannelComp framework, which facilitates the computation of desired functions by multiple transmitters over a common receiver using digital modulations across a multiple access channel. While ChannelComp currently offers a broad framework for computation by designing digital constellations for over-the-air computation and employing symbol-level encoding, encoding the repeated transmissions of the same symbol and using the corresponding received sequence may signif…

This https://arxiv.org/abs/2402.14788 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Expectation Values of Conserved Charges in Integrable Quantum Field Theories out of Thermal Equilibrium
In this work we present a computation of the averages of conserved charge densities and currents of (1+1)-dimensional Integrable Quantum Field Theories in Generalised Gibbs Ensembles. Our approach is based on the quasi-particle description provided by the Thermodynamic Bethe Ansatz combined with the principles of Generalised Hydrodynamics, and we focus on Non-Equilibrium Steady State averages. When considering the ultraviolet (i.e. high temperature) limit of such averages, we recover the famous…

LOAM: Low-latency Communication, Caching, and Computation Placement in Data-Intensive Computing Networks
Jinkun Zhang, Edmund Yeh
https://arxiv.org/abs/2403.15927

LOAM: Low-latency Communication, Caching, and Computation Placement in Data-Intensive Computing Networks
Deploying data- and computation-intensive applications such as large-scale AI into heterogeneous dispersed computing networks can significantly enhance application performance by mitigating bottlenecks caused by limited network resources, including bandwidth, storage, and computing power. However, current resource allocation methods in dispersed computing do not provide a comprehensive solution that considers arbitrary topology, elastic resource amount, reuse of computation results, and nonline…