
Jonathan Wright developed Neon-based AV1 convolution optimizations for the libsdl-org/aom repository, focusing on ARM architectures. He consolidated I8MM and DotProd Neon intrinsics across multiple AV1 kernel variants, including 8-tap and 12-tap horizontal and vertical paths, to improve decoding and processing throughput. His work included refactoring Neon transpose utilities and standardizing stride types to ptrdiff_t, which enhanced code maintainability and reduced memory risks. Using C and assembly language, Jonathan streamlined code paths, removed redundancies, and established robust build and test practices. The result was faster ARM-based video decoding and a more maintainable codebase prepared for future vectorization efforts.

August 2025 summary: Performance-focused Neon-based AV1 convolution optimizations on ARM, plus code maintenance improvements. Delivered Neon I8MM and Neon DotProd optimizations across aom_convolve8* and AV1 kernels av1_convolve_y_sr / av1_convolve_x_sr, covering 8/6/4/12-tap variants to boost decoding/processing throughput. Completed Neon transpose utilities refactor and standardized stride types (ptrdiff_t) to improve maintainability and reduce memory/saturation risk. Consolidated changes across 12+ commits, including removal of duplicate helpers and path optimizations. Overall impact: faster ARM-based decoding/processing, smoother playback, and reduced risk for future vectorization work. Technologies/skills demonstrated: Neon optimization (I8MM, DotProd), ARM performance tuning, C/C++ refactoring, memory-safety practices, and robust build/test discipline.
August 2025 summary: Performance-focused Neon-based AV1 convolution optimizations on ARM, plus code maintenance improvements. Delivered Neon I8MM and Neon DotProd optimizations across aom_convolve8* and AV1 kernels av1_convolve_y_sr / av1_convolve_x_sr, covering 8/6/4/12-tap variants to boost decoding/processing throughput. Completed Neon transpose utilities refactor and standardized stride types (ptrdiff_t) to improve maintainability and reduce memory/saturation risk. Consolidated changes across 12+ commits, including removal of duplicate helpers and path optimizations. Overall impact: faster ARM-based decoding/processing, smoother playback, and reduced risk for future vectorization work. Technologies/skills demonstrated: Neon optimization (I8MM, DotProd), ARM performance tuning, C/C++ refactoring, memory-safety practices, and robust build/test discipline.
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