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The JUNIPER project is developing a framework for the construction of large-scale distributed systems in which execution time bounds can be guaranteed. Part of this work involves the automatic implementation of input Java code on FPGAs,…
In designing distributed and parallel systems there are several approaches for programming interactions in a multiprocess environment. Usually, these approaches take care only of synchronization or communication in two-party interactions.…
A new approach to multiple access based on finite field transforms is investigated. These schemes, termed Galois-Division Multiple Access (GDMA), offer compact bandwidth requirements. A new digital transform, the Finite Field Hartley…
Web programmers are often faced with several challenges in the development process of modern, rich internet applications. Technologies for the different tiers of the application have to be selected: a server-side language, a combination of…
In this work, we propose a Gaussian mixture model (GMM)-based pilot design scheme for downlink (DL) channel estimation in single- and multi-user multiple-input multiple-output (MIMO) frequency division duplex (FDD) systems. In an initial…
Current middleware systems suffer from drawbacks. Often one is forced to make decisions early in the design process about which classes may participate in inter-machine communication. Further, application level and middleware specific…
The last five years have seen the rapid rise in popularity of what we term internet distributed applications (IDAs). These are internet applications with which many users interact simultaneously. IDAs range from P2P file-sharing…
Modelling of multivariate densities is a core component in many signal processing, pattern recognition and machine learning applications. The modelling is often done via Gaussian mixture models (GMMs), which use computationally expensive…
We propose a versatile feedback scheme for both single- and multi-user multiple-input multiple-output (MIMO) frequency division duplex (FDD) systems. Particularly, we propose utilizing a Gaussian mixture model (GMM) with a reduced number of…
The next generation of wireless networks will face different challenges from new scenarios. The main contribution of this paper is to show that Generalized Frequency Division Multiplexing (GFDM), as a baseline of flexible circular filtered…
Today's distributed systems operate in complex environments that inevitably involve faults and even adversarial behaviors. Predicting their performance under such environments directly from formal designs remains a longstanding challenge.…
One obstacle to the use of Gaussian processes (GPs) in large-scale problems, and as a component in deep learning system, is the need for bespoke derivations and implementations for small variations in the model or inference. In order to…
Workflow and serverless frameworks have empowered new approaches to distributed application design by abstracting compute resources. However, their typically limited or one-size-fits-all support for advanced data flow patterns leaves…
Recent developments in the industry of personal computing led to a greater number of the so-called edge devices. Such devices typically do not collaborate or foresee the possibility of collaboration to offer aggregated storage and computing…
In this work, we propose a novel adaptive reduced-rank strategy based on joint interpolation, decimation and filtering (JIDF) for large multiuser multiple-input multiple-output (MIMO) systems. In this scheme, a reduced-rank framework is…
Software architecture consists of series of decisions taken to give a structural solution that meets all the technical and operational requirements. The paper involves code refactoring. Code refactoring is a process of changing the internal…
Multi-modal trajectory generation is essential for safe autonomous driving, yet existing diffusion-based planners suffer from high inference latency due to iterative neural function evaluations. This paper presents MISTY (Mixer-based…
Recent advances in generative artificial intelligence (AI) technologies have been significantly driven by models such as generative adversarial networks (GANs), variational autoencoders (VAEs), and denoising diffusion probabilistic models…
Context: The term reactivity is popular in two areas of research: programming languages and distributed systems. On one hand, reactive programming is a paradigm which provides programmers with the means to declaratively write event-driven…
In this article, a new generic higher-order finite-element framework for massively parallel simulations is presented. The modular software architecture is carefully designed to exploit the resources of modern and future supercomputers.…