1 citations · 1 across the 4 of their papers we have counts for
5 papers
Symbolic Separation: Grounding Deep Agents in Knowledge Graphs for Trustworthy Operational Data Analytics
Baibek Davletiyarov, Junaid Ahmed Khan, Andrea Bartolini
Generative AI promises natural language access to the massive numerical telemetry of data centers and Industry 4.0 installations, yet text-to-query and tool-using agents stay unrel…
Is RISC-V Ready for Massively Parallel Astrophysical Codes?
Jenny Lynn Almerol, Nitin Shukla, Federico Ficarelli +5
We present a performance and portability evaluation of three well-established astrophysical production codes, namely iPIC3D, PLUTO, and OpenGadget3, on a Sophgo SG2044 RISC-V proce…
A Unified Ontology for Scalable Knowledge Graph-Driven Operational Data Analytics in High-Performance Computing Systems
Junaid Ahmed Khan, Andrea Bartolini
Modern high-performance computing (HPC) systems generate massive volumes of heterogeneous telemetry data from millions of sensors monitoring compute, memory, power, cooling, and st…
Assessing Tenstorrent's RISC-V MatMul Acceleration Capabilities
Hiari Pizzini Cavagna, Daniele Cesarini, Andrea Bartolini
The increasing demand for generative AI as Large Language Models (LLMs) services has driven the need for specialized hardware architectures that optimize computational efficiency a…
From Data Center IoT Telemetry to Data Analytics Chatbots -- Virtual Knowledge Graph is All You Need
Junaid Ahmed Khan, Hiari Pizzini Cavagna, Andrea Proia +1
Industry 5.0 demands IoT systems that support seamless human-machine collaboration, yet current IoT data analysis requires deep domain, deployment, and query expertise. We show tha…