Zaman Lantra

About Zaman

Zaman has completed his PhD in Computer Science at the University of Warwick, with the graduation ceremony scheduled for July 2025. His research was fully funded by the Department of Computer Science and supervised by Dr. Gihan Mudalige. He specialized in high-performance computing (HPC), with a particular focus on parallel computing technologies and performance portability.

Before beginning his PhD, Zaman worked at the London Stock Exchange Group Technology as a Specialist Software Engineer, where he was responsible for designing and developing performance-critical software components for equity and derivatives markets. He holds a BSc (Hons) degree in Electronic and Telecommunication Engineering from the University of Moratuwa, Sri Lanka. He also completed a research internship at LiveLabs, Department of Information Technology, Singapore Management University.

Research

Zaman’s research focuses on the development of a domain-specific language (DSL) for unstructured mesh-based particle-in-cell (PIC) simulations. His work addresses the challenges of achieving performance portability on modern heterogeneous HPC architectures.

Abstract

Particle-in-cell (PIC) methods are widely used for modelling the dynamics of charged particles under the influence of electric and magnetic fields. Ensuring the performance portability of PIC applications across emerging heterogeneous HPC systems has become a critical concern for scientific computing. One promising approach is the use of high-level abstractions, such as domain-specific languages (DSLs), which allow domain scientists to describe problems at a high level, while relying on automatic source-to-source translation and code generation to produce efficient backend implementations in MPI, OpenMP, CUDA, HIP, SYCL, and other models.

While a degree of performance portability of PIC codes is obtained through performance-portable programming models such as Kokkos, DSLs for unstructured-mesh PIC simulations remain underdeveloped in the HPC community. Zaman's research introduces a new DSL for unstructured PIC computations, building on the techniques pioneered in OP2, a DSL for unstructured mesh algorithms.

The developed DSL, OP-PIC, supports multiple backends including Sequential, OpenMP, CUDA, HIP, SYCL, and their corresponding MPI-enabled derivatives. Applications written using OP-PIC are automatically translated through a Python-based code generator, which leverages LibClang for parsing and Jinja2 for templated code generation. This approach ensures maintainability, extensibility, and performance portability across diverse HPC architectures.

Github : https://github.com/OP-DSL/OP-PICLink opens in a new window

Tech Stack : C/C++, Python, MPI, OpenMP, CUDA, HIP, SYCL, Kokkos, Legion, CMake, Make, Spack, Arm Forge DDT, GDB, Valgrind, Intel Advisor/VTune, Nsight compute/nvProf, ROCProfiler, SLURM, Bash, Clang.

Teaching

Zaman is a Senior Graduate Teaching Assistant for the following undergraduate modules at the Department of Computer Science.

• CS118 - Programming for Computer Scientists (2021/2022 & 2022/2023) - Java

• CS139 - Web Development Technologies (2021/2022, 2022/2023 & 2023/2024) - HTML, CSS, Python, Flask, SQLAlchemy

• CS258 - Database Systems (2022/2023 & 2023/2024) - Java, PostgreSQL

• MA117 - Programming for Scientists (2023/2024) - Java

He also contributed to academic integrity through exam paper marking for Web Development Technologies (2023 & 2024).

In addition, Zaman is a Support Examination Invigilator (Summer 2023) at the Department of Computer Science.

Publications

• Zaman Lantra, Steven A. Wright, and Gihan R. Mudalige. 2024. OP-PIC - an Unstructured-Mesh Particle-in-Cell DSL for Developing Nuclear Fusion Simulations. In Proceedings of the 53rd International Conference on Parallel Processing (ICPP '24). Association for Computing Machinery, New York, NY, USA, 294–304. https://doi.org/10.1145/3673038.3673130Link opens in a new window

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• S.A. Wright, C. Ridgers, G.R. Mudalige, Z. Lantra, J. Williams, A.Sunderland, H.S. Thorne, W. Arter. 2024. Developing performance portable plasma edge simulations : a survey, Computer Physics Communications. 109123. ISSN 0010-4655. doi:10.1016/j.cpc.2024.109123

• M. A. Smith, S. A. Wright, Z. Lantra and G. Mudalige, "The P3 Explorer: An Open Database of Performance, Portability, and Productivity," 2025 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), Turin, Italy, 2025, pp. 512-517, doi: 10.1109/PDP66500.2025.00079Link opens in a new window

• R. Kumarasiri, A. Niroshan, Z. Lantra, T. Madusanka, C. U. S. Edussooriya and R. Rodrigo, "Gait Analysis Using RGBD Sensors," 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore, 2018, pp. 460-465, doi: 10.1109/ICARCV.2018.8581295.
• Kasthuri Jayarajah, Zaman Lantra, and Archan Misra. 2016. Fusing WiFi and Video Sensing for Accurate Group Detection in Indoor Spaces. In Proceedings of the 3rd International on Workshop on Physical Analytics (WPA '16). Association for Computing Machinery, New York, NY, USA, 49–54. https://doi.org/10.1145/2935651.2935659Link opens in a new window
• Archan Misra, Zaman Lantra, and Kasthuri Jayarajah "Ontology-aided feature correlation for multi-modal urban sensing", Proc. SPIE 9831, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII, 98310A (12 May 2016); https://doi.org/10.1117/12.2225143Link opens in a new window