Niranda Perera is a Senior Software Engineer at NVIDIA with 11 years of experience building high-performance distributed data systems, grounded in a PhD in Intelligent Systems Engineering from Indiana University Bloomington. He leads development of Cylon, an open-source distributed dataframe project, and has contributed performance-sensitive features to marquee projects like Apache Arrow and Spark integrations. His expertise spans HPC, parallel and GPU programming, and big data engineering, with a pragmatic appreciation for business analysis and management accounting that helps translate technical work into measurable outcomes. A background in electronic and telecommunication engineering informs his low-level optimization skills, while a track record of cross-platform native library work shows attention to compatibility and deployment at scale. Based in California, he combines research rigor with production-grade delivery, frequently focusing on core kernels and bitmap/format optimizations that accelerate in-memory analytics.
11 years of coding experience
12 years of employment as a software developer
Bachelor’s Degree BSc Eng (Hons) Electronic & Telecommunication Engineering, Bachelor’s Degree BSc Eng (Hons) Electronic & Telecommunication Engineering at University of Moratuwa
High School Physical Science, High School Physical Science at Nalanda College Colombo
Doctor of Philosophy - PhD Intelligent Systems Engineering, Doctor of Philosophy - PhD Intelligent Systems Engineering at Indiana University Bloomington
Contributions:77 commits, 15 PRs, 6 comments in 1 year 7 months
Contributions summary:Niranda primarily focused on integrating and updating native libraries within the Spark ecosystem. Their commits involve the addition and modification of resource files, specifically native libraries for various operating systems and architectures, related to the snappy compression library and other native dependencies like jansi and netty. These changes suggest a focus on ensuring the correct dependencies are included, potentially improving performance and compatibility of Spark bundles across different platforms.
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
Role in this project:
Back-end Developer
Contributions:103 reviews, 12 commits, 19 PRs in 2 months
Contributions summary:Niranda contributed to the Apache Arrow project by implementing new kernels for string manipulation, including reverse functionality for ASCII and UTF-8 strings, and the if_else functionality, which involves combining arrays based on a boolean mask. They fixed a bug related to the replace_substring_regex kernel and also optimized bitmap operations and casting for dictionary types. Their work demonstrates a focus on improving the core functionality and performance of the data processing library.
memorymulti-languagetoolboxacceleratedarrow
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Niranda Perera - Senior Software Engineer at NVIDIA