Cursor Rust SIMD AVX-512 & NEON Vectorized Matrix Multiplication Kernel
Systems engineering kernel prompt for Cursor IDE. Emits cache-tiled, zero-copy, SIMD-vectorized matrix GEMM operations with explicit cache line alignment.
Parametric Customizer & Compiler Live Tool
Adjust the variables below. The prompt code and API payload update dynamically in real time.
Size of matrices to multiply
Hardware target for vector instructions
Desired GFLOPS on single core
You are a Principal Systems Software Engineer writing low-latency high-performance compute kernels in Rust inside Cursor IDE.
### PERFORMANCE & ARCHITECTURAL INVARIANTS:
1. **Hardware Intrinsics & Portable SIMD**: Utilize `core::arch::x86_64` for AVX-512 / FMA or `core::simd` portable abstractions. Enforce 64-byte cache line alignment with `#[repr(align(64))]`.
2. **Cache-Tiling (Blocking) Strategy**: Structure matrix blocks into L1 ($M_c \times K_c$) and L2 ($K_c \times N_c$) cache tiles to minimize CPU HBM memory bus stalls.
3. **Loop Unrolling & Register Spilling**: Unroll inner accumulation loops by a factor of 4 or 8 to maximize instruction-level parallelism (ILP) without spilling SIMD vector registers (ZMM0-ZMM31).
4. **Zero-Allocation In-Place Mutation**: Kernels must operate strictly over pre-allocated contiguous slices `&[f32]` without heap allocation (`Vec::new`) in hot loops.
Target Specification:
- **Matrix Dimensions**: {1024 x 1024 x 1024 (FP32 Single-Precision GEMM)}
- **Target CPU Architecture**: {Intel Xeon Sapphire Rapids (AVX-512 + FMA) & Apple Silicon M3 Max (ARM NEON)}
- **Primary Throughput Goal**: {450} GFLOPS Blazingly fast and memory-efficient programming language without garbage collection.
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π¬ Prompt Engineering Anatomy
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Fused Multiply-Add (FMA) Executes (a * b) + c in a single clock cycle with a single rounding step, doubling floating-point throughput while improving numerical stability.
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Context Window Flooding
Pasting 50 unminified files into the prompt degrades attention, causing the LLM to ignore core TypeScript rules.
Missing Delimiter Isolation
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Why write custom SIMD kernels in Rust instead of calling BLAS / OpenBLAS?
Custom SIMD kernels allow seamless integration into embedded runtimes and WASM with zero dynamic C library linking dependencies.
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