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cuBLAS & Quantized FP8 Matrix Multiplication in Rust
Zero-Overhead cuBLAS Bindings
While custom PTX is vital for unique activations, dense GEMM (General Matrix Multiply) operations are best delegated to cuBLAS, NVIDIA's hand-tuned assembly library. cudarc exposes native cuBLAS bindings in safe Rust:
use cudarc::cublas::{CudaBlas, GemmConfig, Gemm};
pub fn run_cublas_gemm(
blas: &CudaBlas,
a: &CudaSlice,
b: &CudaSlice,
c: &mut CudaSlice,
m: usize, n: usize, k: usize,
) -> Result<(), Box> {
let cfg = GemmConfig {
alpha: 1.0,
beta: 0.0,
m: m as i32,
n: n as i32,
k: k as i32,
lda: k as i32,
ldb: n as i32,
ldc: n as i32,
};
// Invokes cuBLAS SGEMM with zero pointer allocation overhead
unsafe { blas.gemm(cfg, a, b, c) }?;
Ok(())
}
SYNAPSE VERIFICATION
QUERY 1 // 1
Why is FP8 (e4m3fn) precision widely adopted for transformer inference on modern NVIDIA GPUs?
It cuts memory bandwidth consumption by 50% compared to FP16 while doubling Tensor Core math throughput with near-zero perplexity loss
It eliminates the need for GPU drivers
It allows models to run without CUDA
It converts text tokens into audio waveforms automatically