Collaborative edge-cLoud continuum and Embedded AI for a Visionary industry of thE futuRe

✨ CLEVER’s Research Goals
To enable different levels of communication across distinct infrastructure domains, aiming to safeguard the infrastructure’s security while ensuring its smooth operation. To design a decentralized optimization model that ensures the careful and selective dissemination of information among different providers and operators. To model the inter-dependencies among processing tasks to guarantee various requirements (minimize delay, processing…

🔐 CLEVER Project achieves a world first in post-quantum secure communications!
We’re proud to present the first-ever end-to-end, line-rate optical fiber link using post-quantum cryptography (PQC), implemented with Data Processing Units (DPUs) and demonstrated at 92.3 Gbps! In a hybrid PQC setup using Kyber and Dilithium, we’ve shown that full-stack quantum-resistant encryption can: ✅ Achieve near-baseline throughput ✅ Slash CPU load by 60% via DPU offloading ✅ Operate over…

Deploying Deep Neural Networks directly into network switches? Now it’s possible!
The CLEVER Project presents a novel way to embed AI into programmable data planes — with zero arithmetic logic, zero stateful memory, and zero loss in performance. 🔍 Our latest innovation introduces a lookup table distillation technique that transforms complex DNNs into cascaded, stateless, P4-compatible flow tables — unlocking true in-network AI at wirespeed. 💡…

🚨 Can we trust all the data we feed into AI models?
The CLEVER Project is tackling one of the most critical questions in AI for distributed environments: how do we make machine learning resilient when data comes from a wide range of sources—with varying levels of trust? 📍 Presented at the Cloud Edge Continuum Workshop (CEC23), our latest research explores: 🔹 How trust scores—based on data provenance…

🚀 GVirtuS gets a major boost with RDMA!
We’re excited to present a breakthrough from the CLEVER Project: a novel RDMA over InfiniBand Communicator that significantly accelerates GPGPU virtualization using GVirtuS — enabling smarter, faster, and more efficient AI workloads across remote GPUs ⚡🧠 🔍 Why this matters: Traditional TCP/IP-based GPU virtualization is plagued by context switches and latency. With the new RDMA Communicator,…