Numerous irregular graph datasets, for example social networks or web graphs, may contain
even trillions of edges. Often, their structure changes over time and they have domain …

Cloud computing is new technology that has considerably changed human life at different
aspect over the last decade. Especially after the COVID-19 pandemic, almost all life activity …

Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud
services, and serverless functions have immediately become a new middleware for building …

Simple graph algorithms such as PageRank have been the target of numerous hardware
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …

We introduce a high-performance cost-effective network topology called Slim Fly that
approaches the theoretically optimal network diameter. Slim Fly is based on graphs that …

FPGA has been an emerging computing infrastructure in datacenters benefiting from
features of fine-grained parallelism, energy efficiency, and reconfigurability. Meanwhile …

Graph neural networks (GNNs) are among the most powerful tools in deep learning. They
routinely solve complex problems on unstructured networks, such as node classification …

Machine learning methods have a long history of applications in high-energy physics (HEP).
Recently, there is a growing interest in exploiting these methods to reconstruct particle …

Spatial computing architectures promise a major stride in performance and energy efficiency
over the traditional load/store devices currently employed in large scale computing systems …

Graph neural networks have been shown to achieve excellent performance for several
crucial tasks in particle physics, such as charged particle tracking, jet tagging, and …