7 papers
Avoiding Cross-Datacenter Collective Congestion via Disaggregated Buffering
Mariano Scazzariello, Noga H. Rotman, Dima Gavrilenko +6
LLM training at the scale of tens of thousands of GPUs now spans multiple datacenters (DC), making cross-DC collectives over long-haul links unavoidable. A critical and overlooked…
Blink: CPU-Free LLM Inference by Delegating the Serving Stack to GPU and SmartNIC
Mohammad Siavashi, Mariano Scazzariello, Gerald Q. Maguire +2
Large Language Model (LLM) inference is rapidly becoming a core datacenter service, yet current serving stacks keep the host CPU on the critical path for orchestration and token-le…
Dissect-and-Restore: AI-based Code Verification with Transient Refactoring
Changjie Wang, Mariano Scazzariello, Anoud Alshnakat +3
Formal verification is increasingly recognized as a critical foundation for building reliable software systems. However, the need for specialized expertise to write precise specifi…
Can LLMs Forecast Internet Traffic from Social Media?
Jonatan Langlet, Mariano Scazzariello, Flavio Luciani +3
Societal events shape the Internet's behavior. The death of a prominent public figure, a software launch, or a major sports match can trigger sudden demand surges that overwhelm pe…
Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues
Daniele Cipollone, Changjie Wang, Mariano Scazzariello +4
In today's digital landscape, the importance of timely and accurate vulnerability detection has significantly increased. This paper presents a novel approach that leverages transfo…
From Scientific Texts to Verifiable Code: Automating the Process with Transformers
Changjie Wang, Mariano Scazzariello, Marco Chiesa
Despite the vast body of research literature proposing algorithms with formal guarantees, the amount of verifiable code in today's systems remains minimal. This discrepancy stems f…