Alessandro Morari, Ph.D.
Alessandro Morari, Ph.D.
Building AI Systems from Silicon to Software @NVIDIA
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About
About
I build AI systems across the full stack, from GPU kernel optimization to AI product leadership.
At NVIDIA, I lead efforts in AI-driven GPU kernel development and evaluate next-generation programming models for accelerated computing. Before NVIDIA, I led a team at IBM Research that shipped Watson Code Assistant from research through production, one of the earliest large-scale generative AI products. Earlier: Summit and Sierra supercomputers, distributed runtime systems at PNNL, and I created NYU Courant's first course on High Performance Machine Learning.
30+ publications. 15 patents. Ph.D. in Computer Architecture.
Education:
Education:
Ph.D. in Computer Architecture, Polytechnic University of Catalunya.
M.Sc. in Computer Engineering, University of Rome Tor Vergata.
B.Sc. in Computer Engineering, Roma Tre University.
Awards
Awards
IBM Outstanding Technical Achievement Award (2023) - Watson Code Assistant
IBM Top Technical Talent Award (2023)
IBM Outstanding Division Achievement Award (2018) - CORAL Summit and Sierra Supercomputers
IBM Top Technical Talent Award, 2017
Outstanding Performance Award, PNNL (2014) - Graph Engine for Multithreaded Systems (GEMS)
IPDPS Best Paper Award (2012)
Exemplar People Manager Award, IBM
In the Press
In the Press
CUDA Tile Programming Model (2025)
CUDA Tile Programming Model (2025)
"NVIDIA Introduces CUDA 13.1 with CUDA Tile". Calling it the largest advancement since the NVIDIA CUDA platform was inroduced in 2006, NVIDIA has launched CUDA 13.1 with CUDA Tile https://insidehpc.com/2025/12/nvidia-introduces-cuda-13-1-with-cuda-tile/
AI for Code / Watson Code Assistant (2022-2023)
AI for Code / Watson Code Assistant (2022-2023)
"Red Hat and IBM Research Advance IT Automation with AI-Powered Capabilities for Ansible" - Red Hat and IBM announce Project Wisdom at AnsibleFest Chicago, bringing AI-powered code generation to IT automation https://www.redhat.com/en/about/press-releases/red-hat-and-ibm-research-advance-it-automation-ai-powered-capabilities-ansible
"IBM Launches WatsonX Code Assistant" - IBM announces WatsonX Code Assistant for enterprise application modernization and IT automation https://newsroom.ibm.com/2023-10-26-IBM-Launches-watsonx-Code-Assistant
Summit/Sierra Supercomputers (2018)
Summit/Sierra Supercomputers (2018)
"Two DOE Supercomputers Top List of World's Fastest" - U.S. Department of Energy Oak Ridge's Summit and Lawrence Livermore's Sierra ranked #1 and #2 globally https://www.energy.gov/articles/two-doe-supercomputers-top-list-worlds-fastest
"Sierra honored with Top Supercomputing Achievement" - HPCwire Editors' Choice Award Lawrence Livermore National Laboratory https://www.llnl.gov/article/44896/sierra-honored-top-supercomputing-achievement-hpcwire
"Summit Supercomputer is Already Making its Mark on Science" - HPCwire Coverage of Summit's scientific impact and architecture https://www.hpcwire.com/2018/09/20/summit-supercomputer-is-already-making-its-mark-on-science/
GEMS massively multithreaded graph runtime (2014-2019)
GEMS massively multithreaded graph runtime (2014-2019)
"Startup Trovares Brings HPC to Graph Analytics" - HPCwire Seattle startup commercializes PNNL graph database technology https://www.hpcwire.com/2019/04/16/startup-trovares-brings-hpc-to-graph-analytics/
"A Meaningful Data Miner" - PNNL Science Highlights GEMS framework enables graph queries on billion-triple datasets https://www.pnnl.gov/science/highlights/highlight.asp?id=3949
"PNNL: A Collection of Quality HPC Research at IEEE Cluster 2015" - PNNL High-performance dictionary encoding for RDF datasets https://www.pnnl.gov/science/highlights/highlight.asp?id=4018
Selected Papers
Selected Papers
AI and ML
AI and ML
D2A: A Dataset Built for AI-Based Vulnerability Detection Methods Using Differential Analysis.
ICSE-SEIP 2021
Yunhui Zheng, Saurabh Pujar, Burn Lewis, Luca Buratti, Edward Epstein, Bo Yang, Jim Laredo, Alessandro Morari, Zhong Su.
DOI: https://doi.org/10.1109/ICSE-SEIP52600.2021.00020
Exploring Software Naturalness through Neural Language Models.
arXiv 2020
Luca Buratti, Saurabh Pujar, Mihaela Bornea, Scott McCarley, Yunhui Zheng, Gaetano Rossiello, Alessandro Morari, Jim Laredo,
Veronika Thost, Yufan Zhuang, Giacomo Domeniconi
Transformer-based language models for code analysis and vulnerability identification.
arXiv: https://arxiv.org/abs/2006.12641
VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements.
ICSME 2022
Yangruibo Ding, Sahil Suneja, Yunhui Zheng, Jim Laredo, Alessandro Morari, Gail Kaiser, Baishakhi Ray. Ensemble learning for automated vulnerability localization in source code.
DOI: https://doi.org/10.1109/ICSME55016.2022.00018
Automated Code Generation for Information Technology Tasks in YAML through Large Language Models.
DAC 2023
Saurabh Pujar, Luca Buratti, Xiaojun Guo, Nicolas Dupuis, Burn Lewis, Sahil Suneja, Atul Sood, Alessandro Morari
High Performance Computing and Systems
High Performance Computing and Systems
1. Scaling Semantic Graph Databases in Size and Performance
1. Scaling Semantic Graph Databases in Size and Performance
IEEE Micro, 2014
Alessandro Morari, Vito Giovanni Castellana, Oreste Villa, Antonino Tumeo, Jesse Weaver, David Haglin, Sutanay Choudhury, John Feo
A software stack that relies primarily on graph-based methods to implement scalable RDF databases on commodity clusters.
2. In-Memory Graph Databases for Web-Scale Data
2. In-Memory Graph Databases for Web-Scale Data
IEEE Computer, 2015
Vito Giovanni Castellana, Alessandro Morari, Jesse Weaver, Antonino Tumeo, David Haglin, Oreste Villa, John Feo
High-performance in-memory graph database system for web-scale semantic data.
3. A Quantitative Analysis of OS Noise
3. A Quantitative Analysis of OS Noise
IPDPS 2011
Alessandro Morari, Roberto Gioiosa, Robert W. Wisniewski, Francisco J. Cazorla, Mateo Valero
Developed technique to provide quantitative analysis of OS events that limit application scalability on large-scale supercomputers.
4. Evaluating the Impact of TLB Misses on Future HPC Systems
4. Evaluating the Impact of TLB Misses on Future HPC Systems
IPDPS 2012
Alessandro Morari, Roberto Gioiosa, Robert W. Wisniewski, Bryan S. Rosenburg, Todd Inglett, Mateo Valero
Quantitative analysis of TLB misses on Blue Gene/P at scale (up to 4096 cores).
5. Scaling Irregular Applications through Data Aggregation and Software Multithreading
5. Scaling Irregular Applications through Data Aggregation and Software Multithreading
IPDPS 2014
Alessandro Morari, Antonino Tumeo, Daniel G. Chavarría-Miranda, Oreste Villa, Mateo Valero
Techniques for scaling irregular applications on distributed memory systems.
Presentations and Seminars
Presentations and Seminars
NeurIPS 2020 - AI for Code Expo Talk https://nips.cc/Expo/Conferences/2020/talkpanel/21302
NYU Courant Colloquium https://cs.nyu.edu/dynamic/news/colloquium/1010/
HPCXXL 2017 https://hpcxxl.org/wp-content/uploads/2017/09/HPCXXL-Fall-2017-V6.pdf
PiPhilly AI Event https://www.piphilly.org/it/piphilly-events/video-galleries/ai-event-videos/
Links
Links
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