
During January 2026, this developer contributed GPU-accelerated implementations of the cosh and sinh functions to the modular/modular standard library, addressing the lack of CUDA libm support and improving numerical accuracy for small input values. The work involved designing GPU-friendly algorithms, including a native expm1 implementation and a numerically stable expm1-based approach for sinh. Comprehensive test coverage was added, with accuracy checks across float32, float16, and bfloat16 types in Mojo. Leveraging expertise in GPU programming, mathematics, and numerical methods, the developer enhanced the library’s GPU math capabilities and resolved compile issues, delivering robust functionality for GPU-targeted applications.
January 2026: Delivered GPU-accelerated cosh and sinh support in modular/modular's standard library, enabling GPU targets and improving numerical accuracy for small inputs. Implementations use GPU-friendly formulas (cosh via (e^x + e^-x)/2; sinh via expm1-based approach with rearrangements) and include a native expm1 implementation. This work addresses the CUDA libm limitation and adds robust GPU math functionality. Expanded test coverage includes GPU math tests and numerical accuracy checks across float32, float16, and bfloat16 in test_math.mojo and test_math_accuracy.mojo. The change set closes modular/modular#5719 and is traceable to commit d7de8d66368e0a2be0a2045757fc3063502aa351.
January 2026: Delivered GPU-accelerated cosh and sinh support in modular/modular's standard library, enabling GPU targets and improving numerical accuracy for small inputs. Implementations use GPU-friendly formulas (cosh via (e^x + e^-x)/2; sinh via expm1-based approach with rearrangements) and include a native expm1 implementation. This work addresses the CUDA libm limitation and adds robust GPU math functionality. Expanded test coverage includes GPU math tests and numerical accuracy checks across float32, float16, and bfloat16 in test_math.mojo and test_math_accuracy.mojo. The change set closes modular/modular#5719 and is traceable to commit d7de8d66368e0a2be0a2045757fc3063502aa351.

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