Deric Cheung is a software engineer with 11 years of experience specializing in compilers and graphics tooling, currently developing the HLSL shader compiler at Microsoft within upstream LLVM and Clang. He holds both a BSc and an MSc in Computer Science from the University of Alberta (3.9/4.0 GPA) and has applied his academic work to practical projects such as MLIR proof-of-concepts and compiler fuzz-testing tools. His open-source contributions to the high-profile llvm-project include implementing HLSL intrinsics and improving scalarizer transformations, while his DevOps work on Adoptium streamlined GitHub Actions–driven test workflows. At Huawei he researched Vulkan and SPIR-V instrumentation for hardware-accelerated ray tracing performance, combining low-level compiler expertise with systems performance analysis. Colleagues describe him as a detail-oriented engineer who moves between research and production code, bringing rigorous testing and automation practices to complex compiler toolchains.
11 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Computer Science, 3.9/4.0 GPA, Master of Science - MS, Computer Science, 3.9/4.0 GPA at University of Alberta
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
Role in this project:
Back-end Developer & Compiler Engineer
Contributions:89 reviews, 20 PRs, 4 pushes in 2 months
Contributions summary:Deric primarily contributed to the LLVM compiler project, focusing on HLSL (High-Level Shading Language) features and related code generation. They implemented HLSL intrinsics like `D3DCOLORtoUBYTE4`, `reflect`, and `and`, adding necessary tests and functionality. Additionally, the user worked on the Scalarizer transformation, enhancing its ability to optimize code and adding new tests for verifying its behavior.
Contributions:9 reviews, 11 commits, 11 PRs in 1 month
Contributions summary:Deric primarily focused on enhancing the build and testing infrastructure for the Adoptium project. Their contributions included creating a comment-triggered PR build workflow using GitHub Actions, which parses comments to determine test parameters. They also implemented improvements like whitespace trimming and customized SDK support, and fixed platform mappings. Overall, the user's work centers on streamlining and automating the testing process within the repository.
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