Intro to Practical SIMD for Graphics
19 hours ago
- #Performance Optimization
- #Game Development
- #SIMD
- SIMD (Single Instruction, Multiple Data) instructions allow CPUs to process multiple data points with a single instruction, significantly speeding up operations like matrix multiplication.
- Different CPU architectures support various SIMD instruction sets: x86 (SSE, AVX, AVX512), ARM (NEON, SVE), and RISC-V (RVV), each with unique features and compatibility challenges.
- For game development, targeting AVX2 is recommended for high-end games, while SSE4 ensures compatibility with virtually all PCs. NEON is essential for mobile and Nintendo Switch development.
- SIMD programming can be done using intrinsics, libraries like XSIMD, or ISPC, each offering different trade-offs between performance and ease of use.
- Practical examples include vectorized array addition and 4x4 matrix multiplication, demonstrating significant performance improvements over scalar code.
- Frustum culling can be optimized using SIMD by processing multiple spheres simultaneously, leveraging AVX for 8-wide operations and FMA for further performance gains.
- FMA (Floating Multiply-Add) instructions can provide substantial performance improvements for dot product operations, common in graphics algorithms.