Tamar Christina
Software Engineer at Arm Holdings
Newport Pagnell, England, United Kingdom
Summary
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RockstarTamar Christina is a software engineer with nine years of experience specializing in compiler engineering, functional languages, and runtime systems. She focuses on code generation, performance tuning, linkers/loaders, memory allocators, and architecture enablement, with hands-on work improving AArch64 vectorization in GCC and adding Arm64 intrinsics to the .NET runtime. Her contributions target low-level arithmetic patterns and AdvSimd instructions, yielding measurable improvements in performance and code size for real-world workloads. Based in Newport Pagnell, UK, she brings a pragmatic systems mindset—balancing compiler theory with production-grade toolchain patches. Tamar is comfortable navigating both large open-source ecosystems and the intricate details of instruction-level codegen, making her a go-to engineer for architecture-specific optimization challenges.
9 years of coding experience
English, Dutch, papiamentu, Spanish, French
Github Skills (20)
arcgisruntime10
assembly10
runtimes10
net10
run-time10
vectorization10
vector10
code-generation10
sve10
performance-optimization10
assemble10
assembler10
dotnet-core10
compiler-optimization10
csharp10
Programming languages (8)
Github contributions (5)
dotnet/runtime
May 2019 - Jun 2020
.NET is a cross-platform runtime for cloud, mobile, desktop, and IoT apps.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 reviews, 13 commits, 7 PRs in 1 year
Contributions summary:Tamar primarily contributed to the `.NET runtime` repository by implementing and updating Arm64 intrinsics within the `System.Private.CoreLib` library. This involved adding support for various AdvSimd instructions, including `ReverseElementBits`, `AddAcross`, `ZipLow`, `ZipHigh`, `UnzipEven`, `UnzipOdd`, `TransposeEven`, `TransposeOdd`, `ExtractAndNarrowHigh`, and shift/insert operations, all specific to the Arm64 architecture. The commits focused on codegen, API definitions, and related test implementations, signifying a focus on low-level performance optimization.
dotnetruntimelinuxcsharpxamarin
gcc-mirror/gcc
Mar 2020 - Sep 2022
Role in this project:Back-end Developer
Back-end DeveloperContributions:35 commits in 2 years 5 months
Contributions summary:Tamar is primarily focused on making improvements to the vectorization capabilities of the AArch64 compiler for the GNU Compiler Collection (GCC). Their contributions involve creating and adjusting patterns for arithmetic operations, such as multiplication and division, to enhance code generation. The user's work also includes implementing and testing new optimization strategies for the vectorizer and addressing code generation regressions. These contributions lead to performance and code size improvements for applications that use these arithmetic patterns.
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