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Scientific Data Management Research

Jean Luca Bez

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Jean Luca Bez
Data Management Research Scientist
Scientific Data Division
Berkeley Lab

Jean Luca is a Carrer-Track Researcher in the Scientific Data Management Group at Lawrence Berkeley National Laboratory (LBNL), USA. He is passionate about High-Performance I/O, Parallel I/O, Education, and Competitive Programming. His research focuses on optimizing the I/O performance of scientific applications at the middleware level by exploring I/O Forwarding, I/O Scheduling, and Automatic Tuning and Reconfiguration using Machine Learning techniques.

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Conference Papers

Bin Dong, Jean Luca Bez, Suren Byna, "AIIO: Using Artificial Intelligence for Job-Level and Automatic I/O Performance Bottleneck Diagnosis.", In Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing (HPDC ’23), June 16, 2023,

Hammad Ather, Jean Luca Bez, Boyana Norris, Suren Byna, "Illuminating the I/O Optimization Path of Scientific Applications", High Performance Computing: 38th International Conference, ISC High Performance 2023, Hamburg, Germany, May 21–25, 2023, Proceedings, Hamburg, Germany, Springer-Verlag, May 21, 2023, 22–41, doi:

The existing parallel I/O stack is complex and difficult to tune due to the interdependencies among multiple factors that impact the performance of data movement between storage and compute systems. When performance is slower than expected, end-users, developers, and system administrators rely on I/O profiling and tracing information to pinpoint the root causes of inefficiencies. Despite having numerous tools that collect I/O metrics on production systems, it is not obvious where the I/O bottlenecks are (unless one is an I/O expert), their root causes, and what to do to solve them. Hence, there is a gap between the currently available metrics, the issues they represent, and the application of optimizations that would mitigate performance slowdowns. An I/O specialist often checks for common problems before diving into the specifics of each application and workload. Streamlining such analysis, investigation, and recommendations could close this gap without requiring a specialist to intervene in every case. In this paper, we propose a novel interactive, user-oriented visualization, and analysis framework, called Drishti. This framework helps users to pinpoint various root causes of I/O performance problems and to provide a set of actionable recommendations for improving performance based on the observed characteristics of an application. We evaluate the applicability and correctness of Drishti using four use cases from distinct science domains and demonstrate its value to end-users, developers, and system administrators when seeking to improve an application’s I/O performance.

Jean Luca Bez, Hammad Ather, Suren Byna, "Drishti: Guiding End-Users in the I/O Optimization Journey", PDSW 2022, held in conjunction with SC22, 2022,

Jean Luca Bez, Ahmad Maroof Karimi, Arnab K. Paul, Bing Xie, Suren Byna, Philip Carns, Sarp Oral, Feiyi Wang, Jesse Hanley, "Access Patterns and Performance Behaviors of Multi-layer Supercomputer I/O Subsystems under Production Load", 31st International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC '22), Association for Computing Machinery, June 27, 2022, 43–55, doi: 10.1145/3502181.3531461

André Ramos Carneiro, Jean Luca Bez, Carla Osthoff, Lucas Mello Schnorr, Phillipe Olivier Alexandre Navaux, "HPC Data Storage at a Glance: The Santos Dumont Experience", IEEE 33rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), IEEE, November 26, 2021, 157-166, doi: 10.1109/SBAC-PAD53543.2021.00027

Jean Luca Bez, Houjun Tang, Bing Xie, David Williams-Young, Rob Latham, Rob Ross, Sarp Oral, Suren Byna, "I/O Bottleneck Detection and Tuning: Connecting the Dots using Interactive Log Analysis", 2021 IEEE/ACM Sixth International Parallel Data Systems Workshop (PDSW), January 1, 2021, 15-22, doi: 10.1109/PDSW54622.2021.00008

Tonglin Li, Suren Byna, Quincey Koziol, Houjun Tang, Jean Luca Bez, Qiao Kang, "h5bench: HDF5 I/O Kernel Suite for Exercising HPC I/O Patterns", Cray User Group (CUG) 2021, January 1, 2021,


Jean Luca Bez, Visualizing I/O bottlenecks with DXT Explorer 2.0, Analyzing Parallel I/O (BoF) is held in conjunction with SC22, 2022,

Jean Luca Bez, Where's the Bottleneck?, Berkeley Lab Research SLAM, October 7, 2022,

Jean Luca Bez, Suren Byna, Understanding I/O Behavior with Interactive Darshan Log Analysis, Exascale Computing Project (ECP) Community Days BoF, 2022,

Jean Luca Bez, Towards Understanding I/O Behavior with Interactive Exploration, Berkeley Lab’s Computing Sciences Area 2022 Postdoc Symposium, 2022,

Jean Luca Bez, Visualizing Darshan Extended Traces, Analyzing Parallel I/O (BoF) is held in conjunction with SC21, 2021,