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The input data pipeline is an essential component of each machine learning (ML) training job. It is responsible for reading massive amounts of training data, processing batches of samples using complex transformations, and loading them onto…

There is a growing call for greater amounts of increasingly agile computational power for edge and cloud infrastructure to serve the computationally complex needs of ubiquitous computing devices. Thus, an important challenge is addressing…

The soaring energy demands of large-scale software ecosystems and cloud data centers, accelerated by the intensive training and deployment of large language models, have driven energy consumption and carbon footprint to unprecedented…

Distributed ledgers are a new type of database technology that allows open access to data stored across distributed, decentralised, publicly maintained infrastructures. Current implementations of the such ledgers expect competition between…

The scientific and research community has benefited greatly from containerized distributed High Throughput Computing (dHTC), both by enabling elastic scaling of user compute workloads to thousands of compute nodes, and by allowing for…

The application of Transformer-based large models has achieved numerous success in recent years. However, the exponential growth in the parameters of large models introduces formidable memory challenge for edge deployment. Prior works to…

Cloud computing has made federated database systems (FDBS) significantly more practical to implement than in the past. As part of a recent Web-based Geographic Information System (WebGIS) project, we are employing cloud-native technologies…

Businesses have made increasing adoption and incorporation of cloud technology into internal processes in the last decade. The cloud-based deployment provides on-demand availability without active management. More recently, the concept of…

DenseNets have been shown to be a competitive model among recent convolutional network architectures. These networks utilize Dense Blocks, which are groups of densely connected layers where the output of a hidden layer is fed in as the…

As the volume of data available from sensor-enabled devices such as vehicles expands, it is increasingly hard for companies to make informed decisions about the cost of capturing, processing, and storing the data from every device. Business…

Incorporating computational fluid dynamics in the design process of jets, spacecraft, or gas turbine engines is often challenged by the required computational resources and simulation time, which depend on the chosen physics-based…

This paper explores the role of energy-awareness strategies into the deployment of applications across heterogeneous Edge-Cloud infrastructures. It proposes methods to inject into existing scheduling approaches energy metrics at a…

We seek to enable classic processing of continuous ultra-sparse spatiotemporal data generated by event-based sensors with dense machine learning models. We propose a novel hybrid pipeline composed of asynchronous sensing and synchronous…

A data analysis pipeline is a structured sequence of steps that transforms raw data into meaningful insights by integrating multiple analysis algorithms. In many practical applications, analytical findings are obtained only after data pass…

Modern mobile devices are equipped with high-performance hardware resources such as graphics processing units (GPUs), making the end-side intelligent services more feasible. Even recently, specialized silicons as neural engines are being…

Latency and energy consumption are key metrics in the performance of deep neural network (DNN) accelerators. A significant factor contributing to latency and energy is data transfers. One method to reduce transfers or data is reusing data…

Cloud data pipelines increasingly operate under dynamic workloads, evolving schemas, cost constraints, and strict governance requirements. Despite advances in cloud-native orchestration frameworks, most production pipelines rely on static…

In designing query processing primitives, a crucial design choice is the method for data transfer between two operators in a query plan. As we were considering this critical design mechanism for an in-memory database system that we are…

Next generation of embedded Information and Communication Technology (ICT) systems are collaborative systems able to perform autonomous tasks. The remarkable expansion of the embedded ICT market, together with the rise and breakthroughs of…

We introduce the Quartet of Diffusions, a structure-aware point cloud generation framework that explicitly models part composition and symmetry. Unlike prior methods that treat shape generation as a holistic process or only support part…