Successive Refinement to Caching for Dynamic Content

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The increasing demand for computing power and the emergence of heterogeneous computing architectures have driven the exploration of innovative techniques to address current limitations in both the compute and memory subsystems. One such solution is the use ...

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

We consider the problem of defining and fitting models of autoregressive time series of probability distributions on a compact interval of Double-struck capital R. An order-1 autoregressive model in this context is to be understood as a Markov chain, where ...

Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. Fair distribution of rewards, however, is still a persistent problem in the current generation of decentralized applicati ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query ...

Modern data center fabrics open the possibility of microsecond distributed applications, such as data stores and message queues. A challenging aspect of their development is to ensure that, besides being fast in the common case, these applications react fa ...

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Given two jointly distributed random variables (X,Y), a functional representation of X is a random variable Z independent of Y, and a deterministic function g(⋅,⋅) such that X=g(Y,Z). The problem of finding a minimum entropy functional representation is kn ...

Electric vehicle charging facilities offer their capacity constrained electric charge and parking to users for a fee. As electric vehicle adoption grows, so too does the potential for excessive resource utilization. In this paper, we study how prices set b ...

Context. A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented.Aims. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simula ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

In-network devices around the world monitor and tamper with connections for many reasons, including intrusion prevention, combating spam or phishing, and country-level censorship. Connection tampering seeks to block access to specific domain names or keywo ...

Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilient, adaptive operators. Online processing implies that results are incrementally built as the input arrives, and it is ubiquitous for many applications such ...

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

We study an energy market composed of producers who compete to supply energy to different markets and want to maximize their profits. The energy market is modeled by a graph representing a constrained power network where nodes represent the markets and lin ...

Incidents where water networks are contaminated with microorganisms or pollutants can result in a large number of infected or ill persons, and it is therefore important to quickly detect, localize and estimate the spread and source of the contamination. In ...

Successive Refinement to Caching for Dynamic Content

Chattez avec Graph Search

Intermediate Address Space: virtual memory optimization of heterogeneous architectures for cache-resident workloads

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

On distributional autoregression and iterated transportation

Altruism, reciprocity, and tokens to reward forwarding data: Is that fair?

Secure Interface Design Leveraging Hardware/Software Support

EdgeAI-Aware Design of In-Memory Computing Architectures

Extensions of Peer Prediction Incentive Mechanisms

HPCache: memory-efficient OLAP through proportional caching revisited

uKharon: A Membership Service for Microsecond Applications

Caching and Neutrality

Rebooting Virtual Memory with Midgard

Information Spectrum Converse for Minimum Entropy Couplings and Functional Representations

Resource aware pricing for electric vehicle charging

Fast correlation function calculator A high-performance pair-counting toolkit

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Global, Passive Detection of Connection Tampering

Squall: Scalable Real-time Analytics using Efficient, Skew-resilient Join Operators

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Equilibria in Network Constrained Energy Markets

Estimating pollution spread in water networks as a Schrödinger bridge problem with partial information