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Inspired by the success of Google's Pregel, many systems have been developed recently for iterative computation over big graphs. These systems provide a user-friendly vertex-centric programming interface, where a programmer only needs to…

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems…

Recent feed-forward reconstruction models, such as VGGT, have proven competitive with traditional optimization-based reconstructors while also providing geometry-aware features useful for other tasks. Here, we show that the quality of these…

Nowadays simulations can produce petabytes of data to be stored in parallel filesystems or large-scale databases. This data is accessed over the course of decades often by thousands of analysts and scientists. However, storing these volumes…

In this paper we describe VIG, a data scaler for benchmarks in the context of ontology-based data access (OBDA). Data scaling is a relatively recent approach, proposed in the database community, that allows for quickly scaling up an input…

Advanced image fusion methods are devoted to generating the fusion results by aggregating the complementary information conveyed by the source images. However, the difference in the source-specific manifestation of the imaged scene content…

We present a new Python library called vaex, to handle extremely large tabular datasets, such as astronomical catalogues like the Gaia catalogue, N-body simulations or any other regular datasets which can be structured in rows and columns.…

We introduce Dataset Grouper, a library to create large-scale group-structured (e.g., federated) datasets, enabling federated learning simulation at the scale of foundation models. This library facilitates the creation of group-structured…

Compute-mode rendering is becoming more and more attractive for non-standard rendering applications, due to the high flexibility of compute-mode execution. These newly designed pipelines often include streaming vertex and geometry…

The wide use of XML for document management and data exchange has created the need to query large repositories of XML data. To efficiently query such large data collections and take advantage of parallelism, we have implemented Apache…

The Metaverse represents a transformative shift beyond traditional mobile Internet, creating an immersive, persistent digital ecosystem where users can interact, socialize, and work within 3D virtual environments. Powered by large models…

Vision-Language-Action (VLA) models have emerged as powerful generalist policies for robotic control, yet their performance scaling across model architectures and hardware platforms, as well as their associated power budgets, remain poorly…

Massive data sets have radically changed our understanding of how to design efficient algorithms; the streaming paradigm, whether it in terms of number of passes of an external memory algorithm, or the single pass and limited memory of a…

Automated Machine Learning (AutoML) is an important industrial solution for automatic discovery and deployment of the machine learning models. However, designing an integrated AutoML system faces four great challenges of configurability,…

The rapid integration of vector search into AI applications, particularly for Retrieval Augmented Generation (RAG), has catalyzed the emergence of a diverse ecosystem of specialized vector databases. While this innovation offers a rich…

Serverless computing offers elastic scaling and pay-per-use execution, making it well-suited for AI workloads. As these workloads run in heterogeneous environments such as the Edge-Cloud-Space 3D Continuum, they often require intensive…

Virtualization is a key technology used in a wide range of applications, from cloud computing to embedded systems. Over the last few years, mainstream computer architectures were extended with hardware virtualization support, giving rise to…

Edge computing has become increasingly popular across many domains and enterprises. However, given the locality constraint of edges (i.e., only close-by edges are useful), multiplexing diverse workloads becomes challenging. This results in…

Scalable Vector Graphics (SVG) has become the de facto standard for vector graphics in digital design, offering resolution independence and precise control over individual elements. Despite their advantages, creating high-quality SVG…

The utilization of paging for virtual machine (VM) memory management is the root cause of memory virtualization overhead. This paper shows that paging is not necessary in the hypervisor. In fact, memory fragmentation, which explains paging…